Qualitative social scientists have lagged behind their quantitative colleagues in adopting open social science approaches to research. In their new open access book, “Doing Open Social Science” from LSE Press, Patrick and Timothy outline numerous different strategies that can allow qualitative researchers to better demonstrate the evidence for their work to readers and re-users of their work.

For researchers using qualitative methods open social science can seem to pose far greater difficulties than those faced by quantitative researchers. While replicating a quantitative analysis on the same dataset is relatively straightforward, interviews, focus groups, case studies and fieldwork pose problems for reproducibility because they cannot be repeated. They are necessarily events that are unique in space, time and participants. And yet, text, audio and visual records may allow for re-analysis.

Similarly, boosting pre-registration may appear to require that researchers know in advance and in detail what they will find in the field – whereas interviews, case studies and fieldwork are essentially exploratory approaches. In all qualitative work project teams may set out initial expectations and intentions in pre-registered documents, but they must always remain open and alert to discoveries, new meanings and unexpected developments that shift their research trajectories. Nothing is more fatal for the reliability, integrity and accuracy of qualitative work than researchers who are so constrained by their prior understandings of what happened, what things mean, or how social processes work, that they approach research participants and experiences with closed minds.

Open social science methods can be applied across all the major qualitative methods

In systematic documentation work the existence of records that can be reinspected mitigates reproducibility issues. Pre-registering the scope and intent of the planned research is somewhat easier. But again, the pathways that research takes must adapt to the gains in knowledge that researchers make from immersive reading and intensively analysing texts. In archival work recognition of this imperative has been strengthened amongst historians and social scientists by an acute awareness of the limits of what is recorded and how, which always necessitates critical interpretation of texts. Finally, some pre-registration and disclosure components of open social science approaches may seem to run at a tangent (or even counter) to the growing shift towards co-production and citizen social science.

In our book Doing Open Social Science: A Guide for Researchers we dedicate a whole section to demonstrate how these difficulties are in fact tractable. Open social science methods can be applied across all the major qualitative methods. Indeed, as open social science practices spread and are applied widely and innovatively in qualitative work, so the range of feasible solutions to problems will also expand. The effort needed to translate open practices into qualitative social science can also be productive, stimulating new ideas and creating social science that is trusted by researchers and the public.

Practical steps towards greater openness

We cover here the most frequently used qualitative methods approaches.

Interviews

Only on-the-record interviews can be fully reproducible, while those that are non-attributable or off the record pose substantial problems for researchers seeking to demonstrate that their work is well-founded (Chapter 9). Yet many practical steps can be taken to pre-register the main elements of interview work and to increase assurance about the content of more closed forms of interview. For instance:

- Encouraging interviewees to adopt more open formats, such as blogging on the record, or to shift from off-the-record to non-attributable, or on-the-record interviews (e.g. on Zoom or Teams);

- making better and fuller recordings of what gets said, especially in focus groups and multi-way interviews;

- opening up more information about non-attributable interviews in ‘jittered’ ways that still protect confidentiality, and

- creating quantitative metrics from interview data using innovative methods.

Case studies

Different sets of issues arise around single or very small numbers of in-depth or ‘diagnostic’ case studies, medium numbers of intermediate cases and larger numbers of short ‘apt illustrations’. We show how readers and research re-users can be given strengthened confidence in the work undertaken in each of these situations, especially where cases are anonymized, as they often must be. Key steps involve:

- Being clear about the casing strategy being followed;

- giving enhanced contextual settings for cases, and

- explaining how ‘saturation’ or ‘enough’ numbers for interviews were determined.

And newer methods focus on:

- qualitative comparative analysis (QCA), to explore the logic of multi-causal routes to the same outcomes

- using cases within mixed methods studies, and

-developing comprehensive evidence-synthesising approaches (such as ‘systematic review’ of cases in a given sub-field).

All these approaches can generate valuable extra insights and assurance. Similar steps can also increase the usefulness of fieldwork, as well – for instance, strengthening the immediacy, granularity and later visibility of observations using computerised field journals and notebooks.

Systematic documentation analysis

If the base records being analysed are easily available in full for (digital) reinspection by later project teams, then the potentials for extended forms of reproducibility and re-audit are greater. Researchers can also do a good deal in ‘show and tell’ mode to help readers and re-users understand the character and limits of the original texts being analysed, and to demonstrate that their own interpretation is accurate (Chapter 11). However, where re-accessing the base texts is not possible or practicable, as it often is not, then some similar issues with other qualitative work discussed above may recur. They can again be addressed by:

- adapted forms of pre-registration of the scope and size of work undertaken;

- explaining exploratory adaptations to the planned scope or direction of research;

– curating a selection of key or illustrative documents to help later re-users, wherever feasible;

- counting within and across texts (even if the researchers’ own main approach is immersive reading);

- coding text to make checks on the evidence for qualitative interpretations; and

- 9developing quantitative metrics to back up qualitative interpretations – for instance, via website analyses across multiple agencies or organisations.

Progress in developing the openness of historic archival research has been more limited, with no or scant practicable reproducibility for much older archival evidence However, calls for improving on previously standard but limited historical scholarship methods (footnotes to an archive that readers cannot themselves access) have been made. And ‘digital history’ approaches have greatly diversified options. Although the potential for full digitisation of older historical sources remains vast, social scientists and historians can help develop project-level openness for the materials they use, and help overcome legacy cultural and library constraints in moving archival work into more open practices.

Citizen social science and co-production

These approaches to social science have somewhat divergent aims from open social science for example, by prioritising the privacy/security interests of research participants themselves over demonstrating reproducibility. And some forms of citizen social science (notably deliberative democracy) have paid little heed to openness considerations, although the most participatory approaches have done so. At root, however, both the citizen and open social science and the streams of innovation are similarly aligned in stressing:

- the ultra-careful initial development of research proposals, and

- ensuring that research participants’ meanings and experiences are assigned enhanced importance, are sympathetically documented, and are accurately interpreted with participants’ own involvement.

Looking forward

Over the next ten to twenty years we will likely see a rapid evolution of qualitative research techniques under the impetus of AI and data science improvements, with large language models (LLMs) already revolutionising much of the analysis and production of qualitative research. New research agents will shortly be available to strengthen and better assure the evidence base for qualitative work as academic standards rise in the third digital era wave. The pathways to achieving a higher status and replicability for qualitative social science are already mapped and we are optimistic of the potential for further rapid improvements.

This blogpost draws on Part 3 of Patrick Dunleavy and Timothy Monteath’s book, Doing Open Social Science: A Guide for Researchers, published open access by LSE Press on 14 May 2026. It draws on CIVICA I research funding from the EU’s Horizon Programme.

About the authors

Patrick Dunleavy is Emeritus Professor of Political Science and Public Policy at the London School of Economics and Political Science, and a Fellow of the British Academy and of the Academy of Social Sciences.

Timothy Monteath is Assistant Professor in Data Visualization in the Centre for Interdisciplinary Methods at the University of Warwick, and previously was Researcher on the LSE’s Civica open social science project, where he also completed his doctorate in Sociology.

This text first appeared on LSE Impact blog 13 May 2026

The power of discipline siloes

There is nothing new in intellectuals focusing on narrow fields, as Johnson’s comment about eighteenth century specialisms reminds us. But now the number of fields has never been greater — 170 sub-fields across 19 main subject groupings, according to the UK’s government audit of research, the Research Excellence Framework. And academic subjects have never been more entrenched in their own separation. ‘The first point of identity for most academics is commonly acknowledged to be their disciplinary community or “tribe”’ (McFarlane (2005, p.307; and see Becher and Trower, 2001). Modern disciplines reflect

struggles to limit discourses involved in the production of formal knowledge to a determinate set of objects of analysis, questions about that object, methods of investigation, and modes of demonstration of the nature and determinations of (presumably) these same objects (Amariglio et al, 1993, p.151).

Disciplines create the predominant focii for research funding, exchange of ideas and publishing. And they are avenues of career progression and mutual evaluation.

In modern academia, disciplines typically have three main ‘zones’ marked off from each other by different kinds and pace of changes in their intellectual development (Figure 2.2). The first is a ‘dead heart’ of already developed, thoroughly explored and perhaps ‘worked-out’ subjects. Crucial for teaching and graduate education, this disciplinary core is relatively unchanging. Research in this area may effect incremental alterations, but will typically depend on mobilizing large-scale grants or resources, and in some STEMM subjects undertaking extensive collaborative projects.

One common way in which disciplinary ‘tribalism’ can be fueled is that (left to themselves) academic departments or labs controlled by dominant coalitions (with long-lived staff on tenure track) tend to over-focus on the core ‘dead heart’ area, with most new research clustering on the internal boundary with the zone of moderate advances. Once established this pattern is easily replicated as PhD students and early career researchers are pressed to ‘fit the mould’, while the faster-moving boundary and cross-over areas get neglected. Faculty may tend to ‘man the barricades’, repudiating insurgent ideas from other disciplines and offering dismissive estimates of the prospects for gains from co-operation with colleagues in other subject areas.

Figure 1: Three main zones inside academic disciplines

Yet very rarely is the ‘dead heart’ all there is to the discipline, still less the most intellectually dynamic part of it. Instead, around the heartland area there first lies a zone of moderate advance (shown pink in the Figure). Here ideas are still evolving at a smarter pace. Smaller scale research projects and PhD work are typically concentrated here.

Finally, it is normally at the disciplinary fringes adjoining and overlapping with other academic subjects (shown as purple, green or orange shaded in the Figure) that the pace of advance and innovation is typically fastest, amidst a good deal of intellectual ferment. Younger and more daring researchers will often concentrate in these newly evolving specialisms, constantly having to combat the ‘old guard’ critique that they are diluting the discipline’s pure central stream.

Disciplines and the dynamic knowledge inventory

Whatever the discipline in which it is undertaken, all academic work can be thought of as contributing strongly to a ‘dynamic knowledge inventory’ — a huge and central pool of knowledge, information, expertise, and technologies (Bastow et al, 2014). It contains multiple possible solutions for myriads of actual or possible civilizational problems, and its care and management are hallmarks of a developed society. The inventory is dynamic because it is constantly changing, with new expertise being added and older or less used bodies of knowledge falling out of recognition or recall.

Only a small proportion of the potentially available knowledge is normally being drawn down and used at any given time. But advanced industrial societies in particular have a capacity to rapidly access (or develop) many appropriate solutions, even for radically new or highly intermittent problems. From this reservoir, skilled and motivated businesses, governments, civil society organizations and citizens alike can all draw on information to help them solve problems, plan ahead and conduct or improve their everyday operations. And as Daniel Dennett noted: ‘Scientists have power by virtue of the respect commanded by the discipline’. So this draw-down process has especially favoured well-organized science and technology disciplines.

Universities are not the only, or even the largest, contributors in building the knowledge inventory. Businesses, government agencies, professions, civil society organizations and knowledgeable individuals in many walks of life all contribute. But academics play key roles in testing, conserving and organizing established knowledge, and also in constantly enlarging the inventory by adding new ideas, techniques, and capabilities.

A knowledge inventory is also almost weightless and multi-dimensional. Unlike a physical inventory, the DKI is not costly to maintain for individual contributors and users. And its components have value even when the knowledge involved is not being actively used. The huge stock of latent knowledge included provides additional options and capabilities when needed, the ‘strength in depth’ that especially distinguishes advanced industrial societies from others.

As Figure 2 below shows, the university contributions to the knowledge inventory come in two broad groups, the first and largest taking place inside single disciplines, shown on the left of the Figure. I leave the consideration of the joined-up processes to the next post, and so just focus here on the dominant effects from individual disciplines in each area of work.

Figure 2: How both single-discipline and more joined-up scholarship build up the dynamic knowledge inventory and generate impacts from academic research

Even as we focus down on any particular discipline or subject field, however, it is important to recognize that these fields of endeavour each encompass a number of different types of scholarship. An influential fourfold typology by Ernest Boyer (1990) is shown in the single-discipline box on the left of Figure 1, and in the rest of this post I shall re-package and somewhat renovate Boyer’s categories .

Popular misconceptions imagine that academics are pre-occupied by only one of these types, ‘discovery’ research. So they often give a naïve view of what it takes to make a discipline work. Against this misconception Boyer stressed three other scholarship processes included in the leftmost box — focusing on achieving intellectual integration into coherent wholes, applying academic knowledge to practical issues and problems, and renewal of a given academic profession itself.

Boyer focused on the deeper-lying purposes or rationales organizing academic work within a highly differentiated grid of knowledge specialisms were well explored by Boyer (1990). He stressed that knowledge advances are not a simple matter of making isolated new discoveries — important though these may be. Rather, the development of disciplines is inherently bound up with other key functions — including a scholarship of integrating knowledge across disciplines, a scholarship of applying knowledge in service to wider societal goals, and a scholarship of what Boyer termed ‘teaching’, but which we see more broadly below as ‘renewal’ of the profession. These key insights have resonated widely in the field, and we follow them closely (albeit in a somewhat adapted form) in what follows.

Discovery research

Discovery research seeks to produce specific ‘new facts’ or original insights — although appreciating what is new or significant is itself complex. As Abraham Pais noted: ‘To make a discovery is not necessarily the same as to understand a discovery’. Discovery is by far the most mythologized of scholarly activities, not just in layperson views imagining ‘Eureka’ moments, but even within academic professions themselves. This kind of scholarship is conventionally closely associated with innovation in findings or understanding relationships. Core activities here are shown in Figure 3.

Figure 3: Main components of the scholarship of discovery

Key discovery research methods include:

- Experimental science, uncovering or replicating previously unknown effects under tightly controlled experimental conditions in laboratories. Most physical sciences follow ‘reductionist’ strategies, trying to understand components at the smallest feasible scale, and with knowable laws allowing (relatively simple) aggregation of components.

- Randomized control trials (RCTs) extend an experimental approach to natural, computer, internet, human or societal environments where lab conditions cannot be replicated, because multiple causal relationships are in play simultaneously. Holistic (often chaotic) phenomena here are rarely simply predictable sums of component influences, due to interactions, emergent effects and multiple-level influences.

- Field trips to uncover ‘new facts’, such as expeditions seeking to identify new species or expand knowledge about rare ones, archaeological digs, archival research in history or literary/ cultural studies, and many related forms of investigative effort.

- Database analysis, where already-collected information is interrogated using new mathematical algorithms, models or methods, often drawing on new theories, hypotheses or chains of deductive reasoning. Across all subjects (including the humanities) the scale of modern databases has mushroomed, and internet and web access make information far more globally available.

- New theory development, ranging from focused cogitation in producing maths formulae and theories, through progressively ‘softer’ or more intuitive/interpretive forms of theoretical abstraction and innovation.

Most academics’ and almost all outsiders’ concepts of ‘real’ research focus either on the first item in the first box of Figure 2.3 (core experimentation) or on authoring/writing time — both seen as critical for creativity, ‘genius’ and ‘break-through’ innovations, especially in the physical sciences and technology. Even our listing of ‘core’ activities occupies only the top box in Figure 3, although that shows that the wider landscape of ‘discovery’ activities also includes many elements of academic citizenship, academic management, teaching and achieving impacts. An inter-generational division of labour is often observed in academia, with new discoveries often made by experienced or talented younger researchers, while older academics focus more on creating the multiple conditions for discovery to happen and be understood, and on integration scholarship (considered next below).

Despite its salience and prestige, discovery scholarship, in all its forms above, is not the ‘be all and end all’ of academia. It is not the only ‘core’ research process, set against which all other activities are secondary or dispensable. To do effective discovery research, or even just to secure a few hours of ‘core’ research time to themselves, academics need to create and run well-organised labs and departments; acquire and set-up equipment or access to data; perfect methods (often through laborious trial and error); establish research protocols and ethical permissions; obtain access to relevant survey respondents or sets of personal data; organize field trips or archive visits; create research traditions and detailed institutional expertise and memory; immerse themselves in other people’s forefront research; transfer knowledge; work on publications; organise and attend conferences; develop research grants to escape from teaching for a while; and supervise doctorates. These activities are in no way separate from discovery. They form integral parts of the process of uncovering new knowledge.

In How Institutions Think (1986), the anthropologist Mary Douglas also stresses that it is the professions, research laboratories and academic departments, journals, conferences, funding bodies and other related organizations that jointly govern the internal recognition of ideas in any discipline as novel and worthwhile. Many other, ‘boundary spanning’ organizations (and even individuals) (some involved in the impacts interface discussed in Parts III and IV) control the rate at which innovations and ‘worthwhile’ discoveries are picked up outside academia. In the digital era the scale of such organizational filtering (which Douglas determinedly insists on calling ‘organizational thinking’) is often international, and sometimes global. Yet all too often academics themselves naively dismiss these organizations’ filtering key roles as so much dispensable ‘bureaucracy’.

In the past discovery processes in the physical sciences were far more closely linked to specific technological changes and industrial application imperatives than they perhaps are today. In the era of the most rapid scientific advances (from the 1600s onwards), there were close and integral linkages between pure science, applied science, and technology, especially in wartime — with developments in practitioner fields strongly influencing new scientific advances. Since World War II in many contemporary ‘big science’ fields (especially those covering natural systems, such as particle physics, astronomy or astrophysics), this linkage has been decisively severed. Instead the only conceivable ‘paying customer’ for much forefront research has become national governments, although commercialization of fields like space technology or the internet can happen once serial government funding injections break down long-standing tech barriers (Mazzucato, 2018; National Research Council, 2012). However, in ‘human-dominated systems’ (such as the medical sciences, engineering and computer sciences, design disciplines and the social sciences) a far closer binding of discovery to application persists. For instance, a ‘big pharma’ nexus links multi-national drug companies with medical academics and university hospitals across many countries — providing perhaps the best example of the inter-penetration of industry and academia in knowledge discovery. This reflects the high capital and implementation costs of drugs research, and of meeting regulatory approvals via animal testing, randomized control trials, and other approaches. But important and quite similar clusters occur in knowledge sectors close to defense industries (such as aerospace and materials science), nuclear energy, bio-sciences, agribusiness and cutting-edge information technology.

Corporately organized and team-driven discovery scholarship will have most impact on business where it creates a competitive advantage yielding legally protectable intellectual property assets (like patents), and more immediate or potentially ‘cashable’ gains (Gertner, 2012). Manufacturing and large services firms (as in IT, internet companies and telecoms) expend significant resources in monitoring disciplines where the predominant patterns of knowledge advance mean that such discoveries most often occur, especially in STEMM disciplines. Governments generally follow suit less intensively in pre-commercial areas, but are most active in the defence and medical areas.

Conventional and layperson views often seem to suppose that academic research primarily changes the dynamic knowledge inventory directly via individual or team-based single discoveries. Most media stories (including media releases originated by universities themselves) focus on discrete new findings or inventions allegedly making possible new or changed products or practices in firms, medical services, or even government. A more realistic picture recognizes that even in the physical sciences unmediated (or even clearly traceable) effects from individual research outcomes are very rare. Typically, dozens of cumulative contributions from many different kinds of research have to be brought together by firms or agencies with working knowledge of complex issues to effect any practically useful changes.

We expect discovery research to have much more slender and only episodic influences outside the university sector itself than the conventional wisdom envisages. A great many academic discoveries are inwards-facing to one discipline. They concern the ‘swarms’ of methods, techniques, equipment, routines, and standard operating procedures of academic research itself. Hence, in any discipline, relatively few ‘discoveries’ can be successfully explained or ‘sold’ to an elite audience outside. Even fewer can reach general media or achieve any widespread dissemination (such as the results of new medical or drugs trials) — despite the often misleading efforts of university media offices (see Improving the Impacts of Academic Research, section 8.3; ). Conflicting results and scientific controversies often take the edge off initially promising findings, almost invariably showing that problems, exceptions, by-product effects and possible solutions are more complex than they may appear at first sight.

In human-dominated disciplines also, the rapid evolution of new behaviours by societies and social groups (for instance, the spread of new social practices, use of new internet tools or new environmental threats) often outpaces academic knowledge (Dunleavy et al, 2014). Researchers here can be scrabbling to catch-up with unforeseen changes in social practices and even natural environments, perhaps with few special claims to expertise about them. Across most of the social sciences (and some parts of all human-dominated systems) even the possibility of specific discoveries (especially ‘breakthroughs’) can also be questioned. Developments here rarely follow social ‘laws’ that can be authoritatively validated by ‘professional social enquiry’ or PSI, as Lindblom and Cohen (1979) term it. Instead change is incremental and PSI-validated evidence commonly forms only scattered pinpricks of high quality knowledge across a wide research or policy canvass. Joining-up the dots is essential to find a pattern of any use, but here the only frame for this is ‘ordinary knowledge’. This knowledge consists of specific and valuable expertise of many kinds. It may include some forms of ‘common-sense’, but also many forms of knowing and much accumulated wisdom that contradicts ‘common sense’. Ordinary knowledge may often be well-developed (even esoteric), making sense intuitively or being demonstrably helpful. But it has not itself been scientifically validated. In social systems it is only by combining scientific and PSI results with developed forms of linking ordinary knowledge that we can achieve ‘useable knowledge’.

Integration scholarship

How academics and intellectuals absorb, understand, synthesize, and connect new knowledge garnered via discovery research into coherent theoretical and interpretive knowledge frameworks is critical for many reasons, as the management theorist Henry Mintzberg commented: ‘No generalizing beyond the data, no theory. No theory, no insight. And if no insight, why do research?’ Figure 4 shows a summary of the many activities that go towards this process within a single discipline. Core activities span across the five conventional academic roles, since the disciplinary integration of ideas operates at many levels.

Figure 4: Main components of the scholarship of integration

Although discovery findings are vital, taken on their own they are often not easy to make sense of or act on. At many levels (and not just the conventionally understood macro level), the modern philosophy of science stemming from Thomas Kuhn (1996) argues that all the STEMM sciences and social sciences are shaped by ‘paradigms’, integrating conceptions that help to explain the body of scientific knowledge in the relevant area as a whole. Scientists (and academics in any discipline) often tolerate an extensive accumulation of ‘anomalous’ results inconsistent with the prevailing paradigm. When they cannot be fitted into the accepted, dominant synthesizing paradigm of theoretical explanation, unexpected empirical results are often not taken to directly falsify the current paradigm, but instead often side-lined as ‘puzzles’ needing future solution. This situation may persist so long as there is no competing alternative paradigm that can make sense of both ‘mainstream’ observations and theory, and these known but marginalized ‘puzzles’. In the sciences especially, only a new paradigm can (sometimes) shift established ways of thinking within a discipline.

Integrative work is key in academic disciplines because most intellectual controversy focuses on what is not yet known or agreed. In almost any subject a currently hegemonic paradigm provides a form of professional ‘conventional wisdom’ or the mainstream view. It is often still being critiqued by at least one older ‘legacy’ view, a perspective that was previously hegemonic but has now faded in appeal. Such historic challenges weaken very rapidly in STEMM sciences, but not in the social sciences. The mainstream position is also normally under attack by one or more newly ‘insurgent’ approaches.

Modern STEMM disciplines often have the fewest distinct theory positions (or ‘schools of thought’). They show the least visible professional dissensus internally, following a ‘high consensus, rapid discovery’ pattern where the discipline focuses closely on the research frontier, with prestige attaching chiefly to pushing that forward (Collins, 1994). STEMM disciplines move very swiftly to a strong consensus view of phenomena lying within the frontier itself, and assign lesser status to any remaining controversies there. ‘Softer’ (less mathematical) disciplines, like the humanities and some social sciences, have more enduring debates between long-enduring ‘schools of thought’. In pure humanities disciplines (like philosophy or literature), inter-theoretical struggles still define the ‘commanding heights’ of the discipline. Randall Collins (1998) suggests that an ‘intellectual law of small numbers’ applies in all disciplines, limiting top-level positions to between two and six — two because one cannot disagree with oneself; and six because the ‘Law of Small Numbers’ suggests that any greater differentiation erodes the ability of all the positions in conflict to attract support and to survive inter-generationally.

The importance assigned here to integration scholarship within each discipline also recognizes that most key advances come out of supportive academic environments in which a wide mix of activities, people, skills and favourable organizational structures encourages radical innovations in knowledge structures and ideas and connections. Perhaps the most productive integrator in modern science history was the Nobel-prize winning physicist, Lord Rutherford, whose skillful direction of laboratories at Manchester and Cambridge helped eleven of his close colleagues to win the same prize, across three ‘miracle’ decades for the expansion of physics as a discipline, from 1898 to 1932 (Reeves, 2008). The collective character of integration advances also explains why integrative (and not discovery) social science scholarship has by far the most influence on cultural systems, and knowledge processes in civil society, business and media.

The scholarship of application

Basic theory and empirical knowledge garnered in lab conditions may be well-established, but applying them in concrete and markedly different physical or social situations is far from straightforward. As the history of bridge catastrophes demonstrates, even the best understood knowledge must take full account of the uniqueness of a specific environment, where dozens, hundreds or thousands of system interconnections, constraints and causal processes operate jointly and interact with each other.

The scholarship of application tackles this key set of tasks, but was often looked down on in the past. For example, Henry Rand Hatfield commented in 1924:

I am sure that all of us who teach accounting in the university suffer from the implied contempt of our colleagues, who look upon accounting as an intruder, a Saul among the prophets, a pariah whose very presence detracts somewhat from the sanctity of the academic halls., as Hatfield’s quote above demonstrates.

Figure 5 shows that successful application work also involves many strands of academic activity. All these elements help the specification and differentiation of basic knowledge and research so that it can be meaningfully used to reach an acceptable solution to practical problems and social demands. The originality of such efforts should never be under-estimated. As the mathematician Georges Pólya argued: ‘A great discovery solves a great problem, but there is a grain of discovery in the solution to any problem’ (1998, p. v).

Figure 5: Main components of the scholarship of application

In concrete terms, application scholarship is a substantial share of new grant-funded research in every discipline. It also connects closely to a swathe of university work on externally-defined problems, including basic research and consultancy in government and corporations, design work and prototyping. The complex development of modern civilizations entails that an ever-increasing proportion of academic work is now concerned with ‘human-dominated systems’, spanning beyond what Herbert Simon (1996) called the ‘sciences of the artificial’ and including all the social sciences (Bastow et al, 2014). In such fields the vast bulk of work may fall in or close to the application category, since the development of new knowledge may not change the ‘first principles’ science base much. Instead it primarily extends the remit of basic knowledge to cope with constantly developing forms of human-generated artefacts and social situations

The scholarship of application is particularly important in the modern world — where medicines ‘wear out’ as the organisms targeted develop resistance; where businesses need innovative product features to create competitive advantages; and where public policies must constantly develop in an ‘agile’ fashion to counteract civil society’s capacity to find countervailing responses to previous state interventions. We expect applications scholarship to have far broader and more immediate influences on both business and public policy than the two forms reviewed so far — principally because it tackles more proximate or immediate problems for these sectors. Inherently it must often do so in more ‘joined-up’ ways than highly siloed ‘pure’ research (see Improving the Impacts of Academic Research, Chs 6 and 10).

Renewal of an academic profession

Finding and developing new people with the talent to become senior or experienced scholars is a constant scholarly task in each academic discipline, and in outside professional groups linked to it. The scholarship of renewal inevitably absorbs a large part of academics’ time. And because young researchers are often the most inventive, it connects in integral ways to the vitality of discovery, integration and application.

Figure 6 shows that key tasks here include developing research-led teaching, and helping to supervise and socialise PhD students. Bringing on young researchers in the field is closely bound up with the management of research laboratories and academic departments, together with the creation of inter-university institutions and linkages that can sustain a decentralized process of talent management. The close involvement of senior academics is essential to how all these processes work out.

Figure 6: Main components of the scholarship of renewal

The varying success of different universities and different countries across disciplines closely reflects their levels of investment in renewal processes, and their ability to master the sophisticated knowledge transfer and knowledge management approaches needed for disciplines to grow and flourish. The scholarship of renewal also has a strong and slow-to-change influence on overall academic ‘culture’. In many science disciplines it also has close links with the culture of government and corporate research labs, through them exerting a key influence on overall national R & D achievements.

More broadly though, renewal activities are constantly shaped by the demands of the wider economy and society, since in every discipline academic departments necessarily provide education for undergraduate and even Masters students, most of whom do not go into universities or even other research occupations. Especially for disciplines dealing with human dominated systems, which are in practice almost wholly applied in orientation, there is no hard and fast line between what is needed for outside employment or vocation and what is needed for academic study. Currently in the US more than half of undergraduates complete vocationally orientated degrees, rather than traditional, academically-defined qualifications. The necessary interaction of academic departments with employers in such subjects entails an extended liaison between university teachers and businesses or government.

The scholarship of renewal also carries within it a stream of impacts that are not easily recordable or traceable in the electronic footprints of the digital era, but are none the less real — namely the carrying over of education and socialization from university courses to other sectors, by students moving out of universities and into different occupations. These effects and consequences do not feature further in this analysis, but they are none the less large-scale and important ones, and they operate over considerable periods of time.

Looking at the four forms of scholarship together, in each discipline they cross-influence each other, as shown by the flows inside the fawn box in Figure 2 above. The closest and most frequent feedback is likely to be from discovery scholarship to integration, as new results and relationships expand and morph into accepted understanding in the discipline. In turn, integration activities mostly select (or discard) avenues in discovery, while new theories, ideas, memes and juxtapositions of knowledge suggest a flow of new experiments, field investigations or data analyses that can be attempted. In STEMM subjects especially, many key discovery developments take the form of searches for theoretically predicted effects.

Second, we expect to see a constant and relatively direct feedback loop operating between discovery and application activities. In many STEMM disciplines there are possibilities for patenting processes and applications, extending also to spin-out companies from universities, and increasingly facilitated by expert sections of university administrations or specialist consultancies. Since strong financial incentives may attach to converting discoveries into applications here, the push is especially strong. In turn, new applications and tailored developments often suggest and spur new patterns of investigation of previously accepted knowledge.

The third feedback loop operates from discovery to integration and then via professional renewal back to discovery, with the training of new students (and especially PhDs) for positions in and outside universities functioning as a key stage at which new potentials for discovery are originated. Essentially new cohorts of students bring in new directions in discovery scholarship — and student-based external linkages with industry and society, and with other countries, often sustain them. Plato famously commented that younger people ‘are closer to ideas’ than older folk, perhaps more set in their ways. With less sunk investment in established ways of doing things, younger researchers are characteristically more willing to innovate than their elders. So it is no accident that in many disciplines student-linked and teaching-linked innovations are important stimuli for discovery scholarship — especially in some human-dominated systems where the scope for setting in train ‘social learning’ is strong, such as information technologies (Dunleavy et al, 2014). New integration work also strongly conditions how renewal of the profession operates, changing textbooks or course curricula, and differentiating the education and socialization of new cohorts of graduate students and young researchers — whose arrival at faculty level in turn often leads to methods innovations, new ideas and fresh discoveries.

Conclusions

The categories of scholarship formulated by Ernest Boyer (1990) are valuable as a starting point, but they are too limited in several ways. He defined scholarly integration only as pooling knowledge across disciplines, but clearly most scholarly integration occurs at the stage of pulling together ideas and concepts into coherent theories or ‘world views’ within particular disciplines. Similarly, application scholarship forms a very large part of any discipline’s activities (Stokes, 1997), going far beyond Boyer’s stress on academic service (which we see as just one form of ‘bridging’ activity). This is especially the case in disciplines focusing on ‘human-dominated systems’, a broad category that includes engineering, design, IT and computer sciences, and medical sciences, along with all the social sciences and most parts of the humanities (Dunleavy et al, 2014). Finally, the primary intellectual function served by Boyer’s ‘scholarship of teaching’ is actually a far broader ‘renewal of the profession’, inducting some of the best students to actually join the discipline and so keep its traditions and academic development alive. The sifting of new talented people, and their socialization and incorporation into the discipline, is a set of activities that includes but also extends far beyond teaching alone.

So Figure 7 shows a revised version of Boyer’s categories as four fundamental types of single-discipline scholarship, and summarizes the discussion above of the main types of academic activities involved in each.

Figure 2.7: Overview of how activities linked to four fundamental types of scholarship within single disciplines spread across conventionally recognized academic tasks

About the other blogposts in ‘The Foundations of Academic Organization’ series

Published posts

Post 1 is a short introduction explaining the series’ overall aim of establishing some hopefully better foundations for new and established researchers to think in a more grounded or disciplined way about how academia works, the roles of disciplines and universities, and the operations of academic careers.

Post No 2 Very briefly and synoptically sketches how modern academic life and universities have evolved (over several thousand years) by embodying layers of different knowledge institutions.

Posts still to come in the next few weeks…

Post 4 looks at the importance of discipline-bridging processes — the main circuits by which inter-disciplinary work gets done, and some of the disciplinary potential for over-siloing gets modified.

Post 5 then considers the endemic competition amongst researchers and scholars, and how that relates (perhaps in unstable ways) to the co-operative and collegial elements of academia.

Post 6 considers how academic competition and collegial working both translate into the diverse career trajectories that operate within universities and disciplines.

Post 7 finishes the series by briefly exploring modern universities as bureaucratic organizations, and showing that their ‘governance’ arrangements are perhaps not as unique as academics like to suppose.

I hope that you’ll stay tuned!

Further resources

An in-depth treatment of the themes related to this series of posts is given in Patrick Dunleavy and Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press).

Academic knowledge institutions developed piecemeal over centuries, yet each of seven pre-modern phases have left us with ‘legacy’ practices that are still with us today. Modern academia is thus a ‘layer cake’ of different ways of doing research.

Academic development is cumulative. ‘An educated mind is, as it were, composed of all the minds of preceding ages’, said Bertrand de Fontanelle. For the last two centuries western academics themselves have espoused over-simplified ‘linear progress myths’ of science history and of university practices in general. In such accounts past advances in knowledge depended on intellectuals stripping aside thick layers of common sense misconceptions, mythic beliefs and irrationality. As these barriers were progressively eroded by the ineluctable progress of enlightenment, so the way opened up for disciplined (reductionist) thinking, rigorous experimental and empiricist methods and logical theory construction.

And, of course, the ‘western’ history for many decades ignored academic developments and innumerable contributions from all the non-Western scholarly traditions and civilizations, especially those in Africa, the Islamic world, India, China and south-east Asia. This picture has only recently begun to change in partial ways — with some belated coverage of science and Islam, Asian universities, China’s universities’ survival across civil war and revolution, and modern efforts to integrate Chinese and western approaches.

The western ‘grand narrative’ also over-simplified and filleted out many inconvenient bits of the much more complex and multi-layered stories on which it rested. For instance, it generally omitted hundreds of ‘inconvenient truths’ — such as the manic obsessions of Isaac Newton, who wrote more than two million words of alchemical musings and also believed himself uniquely gifted by God as a biblical scholar; the frenzied work of Fritz Haber in developing poison gases for German use in the trenches of the Western Front; or the determined advocacy by John Neumann of a pre-emptive thermonuclear attack on the Soviet Union in 1950. A veil was mostly drawn over many such less reputable aspects of scientific endeavour, apparently inconsistent with the ‘advance of rationality’ story.

This tendency to simplification is deep-rooted. For much of human history an alternative ‘grand narrative’ held sway, the belief in a ‘golden age’ of classical thought that was once extant and now is in large part lost. In this view, contemporary endeavours should concentrate only on recovering as much as possible of past ‘authorities’ and paradigms. New work should only elaborate knowledge, interpretation or designs only within the confines of classical knowledge and texts. Echoes of this former stance still live on in many humanities disciplines (see the quote from Oakeshott in the first post of this series), and of course in wider religious and cultural attitudes. This view too had multiple inconvenient truths — such as the coexistence of outstanding intellectual advances in Greek times with slavery, the suppression of women, intense tribal feuding, and belief in multiple myths.

Accordingly much post-modern thought stresses as a corrective the need to disbelieve all grand narratives. Instead we should recognize that multiple disjunctures, regressions, inconsistencies and paradoxes occur in the evolution of knowledge and ‘civilization’ as we currently understand them. As a result, to offer any brief or synoptic account of knowledge development is fraught with perils.

Yet with these cautionary words I will go ahead with a sketch summary anyway, drawing on the fascinating 2009 book, Reinventing Knowledge: From Alexandria to the Internet by Ian McNeeley and Lisa Wolverton. They focus on how a sequence of knowledge institutions developed in the ‘West’, and their account is useful for showing how modern higher education practices were built up across many centuries. Figure 1 shows a slightly adapted summary view. [Nevertheless, I should again immediately note that their account (and equally mine here) does not cover changes within, and contributions from academia in all non-Western universities and civilizations — see paragraph 3 above. Readers should bear in mind this substantial caveat].

Figure 1: Key institutions and ‘toolkits’ in the growth of academic knowledge

Note: The timeline here is illustrative only. The diagram draws on the analysis in McNeeley and Wolverton (2009).

In the ancient (Mediterranean) world a critical development was the setting up of the Library at Alexandria by Demetrius of Phaleron, under the patronage of Ptolemy II as an attempted comprehensive knowledge store. It grew into an effort by the post-Alexander Greek pharaohs to acquire copies of all known books and to preserve them, including forcibly seizing and copying books from all visitors to the city. Associated with the Library, scholars were attracted by tax breaks to work in the accompanying Museum, and to debate and understand the books. But the main impetus was still towards creating a mostly passive or latent knowledge store (albeit one with universal ambitions).

The image and legacy of the Library for all subsequent knowledge modes was potent. For researchers who don’t go to labs or use complex computers and equipment, the library long seemed almost the ‘be all and end all’ of university life. By the late nineteenth century, the historian Thomas Carlyle still argued that ‘The true university of these days is a collection of books’. And in the 1950s the American novelist Shelby Foote reputedly said (even less plausibly) that ‘A university is just a group of buildings gathered around a library’. In fact these attempts to identify a social institution with one of its tools or related services are badly misplaced. But they do at least demonstrate the enduring nature of the library as a hub for organizing knowledge.

The collapse of the ancient western civilizations threw a key role in preserving knowledge and documents onto religious communities, monasteries, as much in Europe as in their long-lived roles in Asian civilizations. For many centuries the emphasis was on the copying of texts and authorities. In Europe this was also sustained by significant interchanges of scholars and manuscripts. These exchanges progressively helped to pool knowledge and created networks of thought within the single, religious worldview that prefigured later exchanges. An early ‘Carolingan renaissance’ in Europe (associated with Charlemagne and his successors’s period of western empire) centred on monasteries, yet involved drawing on Greek thought from centuries before according to Hannah Arendt. As Figure 1 indicates, however, monasteries did not sustain their role much beyond the Reformation and its aftermath, with Protestant states abolishing them and sequestering their assets. Even Catholic monarchs cast envious eyes on church assets and landholdings. And the centers of intellectual work had anyway mostly moved to urban universities, although scholarly work by new orders like the Jesuits formed an important part of the counter-Reformation.

The first sustained period in the development of universities in Europe was from the twelfth to the sixteenth centuries, initially as clerically-dominated institutions, but later as centers for more humanistic knowledge of classics, mathematics, medicine, science and even history. By Renaissance times these subjects were seen as key foundations for new urban professions such as law, accounting, architecture, engineering, and more organized military careers. Initially unified internationally via the prevalence of Latin and common religious beliefs, the universities flowered briefly as cradles of newer thought, for a period outside clerical influence. But the religious division at the Reformation soon combined with the ascendant capacity of the new absolute monarchies in Europe to close down debate. Clerical control reasserted itself in protestant and Catholic countries alike, under the post-Westphalian system as kings and emperors sought to re-fashion universities as much as the national religion to serve the princely state’s purposes (and the nation state in large integrated countries, like the UK and France). A wave of malaise spread in many countries’ university systems from the late sixteenth century onwards. Where each monarch chose and controlled their state’s religion, universities often became little more than closed finishing schools for the state’s pastors, with intellectual advances clinging on only in the discreet marginal work of some individual professors.

The next phase was the ‘Republic of Letters’. Playing a central role in the Enlightenment, it operated via the development of extensive correspondence networks between hundreds of intellectuals, who managed to set up knowledge exchange even across hostile or warring state boundaries. Their efforts created an integrated knowledge system spanning the deeply conflicted European communities of faith. Many of the correspondents in this continent-spanning network had no formal role within universities, and some were far removed from the restrictive clericalism of what was taught there. Many were merchants, ‘gentlefolk’ or aristocrats of sufficient means to be able to pursue intellectual work for its own sake, or they increasingly made their living from being independent authors or intellectuals. The focal points of the new networks were the major urban centers and capital cities, and they often involved court officials and politically powerful aristocrats. By the eighteenth century they even included intellectually interested and exceptional monarchs themselves in important roles as ‘active sponsors’, such as Frederick the Great in Prussia and Catherine the Great in Russia.

Integral to the ‘Republic’s’ operations were new institutions, such as newspapers, pamphlets and coffee houses in London, and salons in Paris and many other cities. Learned societies operating under monarchical or aristocratic patronage (such as the Royal Society in London) emerged to act as clearing houses of the new knowledge. They became key forums for the presentation of papers and ideas, again often remote from universities and their moribund curriculums. Of course, at the time these new journals and proceedings (like the correspondence network itself) included a great deal of nonsense and garbled reasoning. And fashions, fads and aristocratic interventions often deformed the development of knowledge. But the Republic of Letters was nonetheless a critical mechanism for more than three centuries.

Although its informal networks were later superceded as a main engine of intellectual change by the revitalization of universities, its impacts lived on in the growth of professional societies and the enduring stress on the full internationalization of knowledge, especially in the physical sciences and mathematics. Today’s massively disciplinary conference circuits, international academic visiting fellowships, academic journals, specialist newsfeeds and newsletters are all prominent re-purposing of institutional forms and tools first developed in this period. Some commentators even detect a new ‘Republic of Blogs’, fueled by open access journals (and the huge successes of the wider open source movement, and boosted by social media. These developments have clearly begun to foster greater cross-disciplinary learning and a re-democratization of knowledge. They also begin to address some of the core malaises afflicting modern universities (like high fees, restricted social access, and extreme dependence on corporate or government funding.

At the end of the eighteenth century and in the early decades of the nineteenth, modern academic disciplines began to be defined in the decentralized political climate of non-unified Germany. Here multiple urban universities were each associated with different principalities and states, and competed for attention and prestige in a highly cultural general atmosphere. Most people today think of disciplines as emerging piecemeal from the fragmentation of the previous ‘natural philosophy’ conception of an integrated science. And there certainly were many important developments tending to differentiate separate sciences out from each other at this period. But Peter Watson shows that in fact the central impetus for modernist disciplinary specialization in Germany came not from the sciences but from classics, philology (the study of languages), archaeology, history, philosophy, theology and comparative religion. It was in these high-prestige humanities subjects that German universities first developed many key elements of academic work that we now take for granted. The disciplinary model and the idea of a research university spread rapidly across all the German states. Its huge scholarly successes in fields like interpreting ancient languages, developing careful archaeological findings, creating a scientific approach to psychology and promoting innovative philosophical thought all ensured its success.

A foundational element was a form of scholarly ‘reductionism’, a focusing in detail on a single part of a process or problem (e.g. translating an unknown ancient language), and an insistence on building up theory from secure and validated micro-foundations. Key innovations in forming disciplines that started in Germany included:

- highly formal and systematized processes for assembling knowledge via intensive and exact collection of evidence and data, which could be permanently and securely stored;

- comprehensively documenting findings in archives and libraries;

- presenting theories and findings for critical debate in formalized seminars, with rigorous rebuttals and criticisms;

- formal post-graduate training, with strong supervision;

- the introduction of a rigorously guarded PhD qualification as a sine qua non for an academic career;

- publishing results in refereed journals, with high entry standards, critical peer reviewers and vigorous post-publication commentary.

Mathematics also shared strongly in these new developments.

Taken together these elements created a ‘research university’ model that endures in many essentials today. Immanuel Kant argued in his 1798 The Conflict of the Faculties (p. 23) that ‘it was not a bad idea to handle the entire content of learning by mass production, so to speak, by a division of labour, so that for every branch of the sciences there would be a public teacher or professor appointed as its trustee, and all of these together would form a kind of learned community… the university’. So humanities disciplines and sub-disciplines proliferated, and new departments and academic professions came to be set up alike in new city universities and long-established centers.

The new model was not without its drawbacks and critics, even early on. Friedrich Nietzsche, who started out in philology and tried being a professor in this highly competitive and discipline-bound system, but gave up, later satirized it in his Twilight of the Idols, aphorism 29:

‘From a doctoral examination:

Q: “What is the task of all higher education?” A: To turn men into machines.

Q: “What are the means?” A: Man must learn to be bored.

Q: “How is that accomplished?” A: By means of the concept of duty.

Q: “Who serves as the model?” A: The philologist: he teaches grinding.

Q: “Who is the perfect man?” A: The civil servant’.

Within half a century the German model of academic organization swept most of Europe. Predictably, the last bastions of the old, religion-linked and debased university models remained Cambridge and Oxford — but even its official history noted that ‘by the end of the nineteenth century Oxford, too, would have to accept that research had a part to play in the university’s life’ (see the impossibly costly 1997 book edited by Brock and Curthoys, p.131). In the USA the influence of the research university idea was equally rapid and pervasive from the late nineteenth century onwards, swiftly displacing the ‘gentlemanly amateurism’ and clericalism of earlier epochs with a rigorous, secular model that fitted well with claims for a new American civilization.

In the STEMM sciences disciplinary developments were equally swift. As restrictive university organization models crumbled, the stage was set for a scientific revolution to create and organize multiple new branches of knowledge. The development of both scientific laboratories and industrial laboratories (also strong in Germany) swiftly followed. Labs were places to conduct fully documented empirical tests and investigations of single processes in carefully controlled conditions. The success of reductionist empirical science, and of atomistic and evolutionary theory, was charted in a huge expansion of scientific and technological knowledge. The rapid development of close linkages between science, maths and technological and medical progress also created a huge prestige for the STEMM disciplines (science, technology, engineering, mathematics and medicine). Two world wars and the Cold War completed the transition of major American campuses to a much larger scale and government-funded ‘research university’ model, fueled by extensive public funding of STEMM sciences and defence-related technologies. These links are still strongly developing and evolving to this day.

Almost from the outset, however, the application of scientific knowledge required not just controlled conditions and careful testing in closed laboratory conditions, but also the extension of controlled field investigations into very different, outside situations. The tools needed here were partly organizational, the ability to impose uniform observation and treatment conditions in the field, remote from laboratories. They lead researchers well outside the lab, as with Pasteur’s pioneering investigations of inoculation against anthrax. They were swiftly followed by many successive and radical improvements in hospital operations and public health policies. The other key tools were statistical analysis techniques, which progressively helped researchers to assess probabilities and to distinguish causal influences from multiple ‘confuser’ variables in multi-causal field settings. A long period later, from the 1950s especially, the development of randomized control trials played a key role in medical and drug development, extending experimental methods into realms (like human physiology) where lab controls were infeasible.

The growth of well-informed and systematic research into social processes drew extensively key social science theories and expansions of understanding, but also on the societal applications of statistics and empirical analysis techniques from the STEMM sciences. Between the 1880s and the early 1950s the evolution of reasonably accurate economic analysis of business cycles, the development of pretty reliable social surveys and opinion polls, and the extension of social psychology, all created radically changed organizational and societal self-knowledge capabilities within advanced industrial societies. Combined with rapidly expanding capabilities in organizational analysis and design, they made feasible huge increases in social control capabilities — changes that have been variously characterized as liberating or oppressive. The social sciences are still developing rapidly, albeit within a disciplinary structure little changed since the 1890s. The reliability and scale of their contribution to knowledge remains disputed in many quarters. But demand for social science research in many economic fields across finance, consultancy, and the public services is strong. And the interaction between physical and social sciences has clearly been productive of improved understanding across a huge swathe of social and ‘human-dominated systems’, even in ‘classic STEMM science’ fields like medicine, ecological and environmental control, engineering and IT.

Finally Figure 1 above shows digitization as potentially inaugurating a new phase in the development of research and higher education. A key development here is the immense speeding up and pooling of data gathering, especially the advent of ‘big data’ from the administrative transactions of companies and governments, machine learning and artificial intelligence, and the ability to conduct online randomized control trials on organizational and communication issues in real time. Within higher education itself the import of digitization is still fiercely disputed. Some critics argue that these apparently new practices are just a blip that will soon pass, leaving higher education relatively little changed. Others see a major, perhaps revolutionary potential.

Pessimists see digital changes as threatening established academic institutions and processes (such as peer-reviewed and ‘closed-access’ journal publishing, and expert in-person tuition) with a form of destructive change called ‘radical disintermediation’. Essentially this means ‘cutting out the middle man’ and commodifying what remains in fewer, standard, mass-disseminated and lower-grade ‘higher education’ packages. The history of ‘disruptive innovation’ across many other industries (not all exposed to digital changes) suggests a bleak future for high cost higher education.

Optimists argue that this bleak picture is overdrawn, and that ‘legacy’ modes of working (such as, mass lectures, in-person classes, and reading paper books) are more resilient. Some optimists see a new digital paradigm for knowledge-development that is faster, cheaper, more open and more democratized than current elite university provision — the theme of Chapter 7 in my 2021 book with Jane Tinkler.

Conclusions

Academic knowledge has been developed historically via at least seven main phases of ‘knowledge institutions’, and their associated enduring intellectual meta-toolkits. From ancient to Renaissance times the key institutions were successively ancient libraries, monasteries, the first phase of mediaeval and then city-based universities, and then the cross-national ‘Republic of Letters’. More modern achievements have been strongly shaped by the emergence of separated academic disciplines and the global dominance of a western ‘research university’ concept — centering around rigorous peer review, the use of laboratories and controlled field work, and the development of social science understanding, statistics and social control. A potential (but still disputed) eighth phase may have begun via digitization. No part of developing current ways of doing things has been anomalous or dispensable. New practices have generally both overlain and eroded what worked from earlier periods.

About the other blogposts in ‘The Foundations of Academic Organization’ series

Published posts

Post 1 is a short introduction explaining the series’ overall aim of establishing some hopefully better foundations for new and established researchers to think in a more grounded or disciplined way about how academia works, the roles of disciplines and universities, and the operations of academic careers.

Posts still to come in the next few weeks…

Post 3 considers the main engine-rooms of scholarship, which are academic disciplines. I look at the tasks that pre-occupy university researchers, shape their distinctive culture, and (according to some critics) generate siloed views of the world.

Post 4 looks at the importance of discipline-bridging processes — the main circuits by which inter-disciplinary work gets done, and some of the disciplinary potential for over-siloing gets modified.

Post 5 then considers the endemic competition amongst researchers and scholars, and how that relates (perhaps in unstable ways) to the co-operative and collegial elements of academia.

Post 6 considers how academic competition and collegial working both translate into the diverse career trajectories that operate within universities and disciplines.

Post 7 finishes the series by briefly exploring modern universities as bureaucratic organizations, and showing that their ‘governance’ arrangements are perhaps not as unique as academics like to suppose.

I hope that you’ll stay tuned!

Further resources

An in-depth treatment of the themes related to this series of posts is given in Patrick Dunleavy and Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press).

You may also find useful my @Write4Research Twitter feed, which pulls together a wide range of the recent discussions relating to academic writing, university organization and academic impacts.

Patrick Dunleavy

Perhaps the most depressing maxim of the normally upbeat philosopher Daniel Dennett is: ‘A scholar is just a library’s way of making another library’. The quote perfectly captures the feeling that a lot of us may fall prey to in our dark moments, the suspicion that academia (and even science) is only a self-perpetuating game, played for kudos by adults who never left school.

To combat such worries, it can be useful to go back to basics and re-address some questions that those of us newly immersed in the bowels of the ‘machine’, or inured to the status quo around us, can take for granted. Questions like: How did research in higher education come to be organized as it is now? And what is the rationale for the way that things are currently set up? These questions also now have a sharp practical import because so many established academic practices are being probingly tested by new digitally-based ways of doing things, a theme that runs through all the chapters in our main book.

Disciplines and universities have tended to give severely deficient answers to these queries, answers that are both rather myopic and self-serving. The official responses often focus on (myths of) their own history and development, and on tendentious ‘fairy tales’ of influence that exaggerate each institution’s, discipline group’s or subject’s role and salience. Consider, for instance, two sharply contrasting ‘mission statements’ by two astute twentieth century intellectuals. For the sciences advocate Alfred North Whitehead (1938, p.171):

‘The task of a university is the creation of the future, so far as rational thought and civilized modes of appreciation can affect the issue’.

But for the conservative philosopher, Michael Oakeshott (1962, p.194):

‘A university is … engaged in caring for and attending to the whole intellectual capital which composes a civilization. It is concerned not merely to keep an intellectual inheritance intact, but to be continuously recovering what has been lost, restoring what has been neglected, collecting together what has been dissipated, repairing what has been corrupted, reconsidering, reshaping, reorganizing, making more intelligible, reissuing and reinvesting’.

Notice that here innovation is almost completely absent in Oakeshott’s antiquarian (almost anti-scientific) listing of university tasks, whereas for Whitehead that is what universities are all about. But both hugely overstate the importance of universities in securing a ‘rational’ future or ‘the whole intellectual capital’ of a civilization.

In modern society civilizational components and rational thought are created and built up by myriads of ‘knowledge workers’ in the professions, businesses, cultural and media organizations, governments, civil society groups, and by independent writers and researchers Their combined roles far outweigh the ‘civilizational’ roles of universities. After a brief ‘golden age’ of academia’s predominance from the late nineteenth century to the 1930s charted by Regis Debray, many key motors of knowledge advance have long since passed beyond academia, as the development of technology, media, culture, design and the internet constantly remind us in recent times. None of this is to deny the importance of university science and technology as motors of contemporary advances, nor the salience of scholars in contemporary society. But both the limits and the successes of universities are grounded in their complex development, prestige systems and governance.

The post-war growth of higher education, and the development of globalization up to 2016, have meant that universities and academic life have been transformed. Compared with conventional businesses, universities have achieved extraordinary relations with their ‘customers’ (students) and ‘ex-customers’ (alumni), creating loyalties of an enduring strength and intensity that few firms can imitate. Over long periods alumni and other donations have built up gigantic endowments of shares, property and land for some established universities (like Harvard, Oxford or Cambridge) that provide a level of long-lived economic security that few capitalist corporations can emulate. The biggest players in the university world are still not multi-national, but grounded typically in one main location. Yet they are nonetheless large economic actors now in terms of their assets and the scale of their capital investments. Major US, UK and European universities, command ‘brands’ with multi-million dollar commercial values.

Above all, while the fortunes of business corporations are pretty volatile, all 2,500 universities work towards the goal of becoming very long-lived, perhaps ‘immortal’ organizations, a status that some top universities seem to have attained already. Accordingly universities tend to take a long view of their activities, investments and reputational development, despite the increasing levels of staff and student transfers between them, and the growth of stronger international competition for students and sources of finance.

Paradoxically, however, despite these many successes, outside critics (especially in business) have often portrayed universities as weakly run and led. Most universities apparently have only a tentative handle on shaping how their staff conduct their teaching. And the doctrine of academic freedom implies that they cannot (legitimately or easily) direct how their academics choose to allocate their research time. Because of the strength of academic collegiality and professionalism, the governance arrangements of higher education institutions can seem to be (and often may in fact be) exceptionally decentralized and loosely integrated. They also have many complex (seemingly Byzantine) features.

To grasp how the academic and external impacts of university research mesh with these background factors, both as they are at present and as they may be in the near future, it is important to consider some complex and long-term influences that shape how contemporary scholarship and academia operate. Even most people long used to academic life can have only a fragmented view of how it operates, and how universities work and are governed — typically one shaped most by their own experience of a given discipline and of the universities where they have worked. Most PhD students, and many early career researchers, have to focus so hard on their primary research that they have not thought that much about these issues.

All this is by way of introduction to a series of six more posts coming in the next few weeks called The Foundations of Academic Organization

All the posts seek to establish some foundations for newbies and even perhaps established researchers to think in a better grounded or more disciplined way about how academia works, the roles of disciplines and universities, and the operations of academic careers.

Published posts

Post No 2 Very briefly and synoptically sketches how modern academic life and universities have evolved (over several thousand years) by embodying layers of different knowledge institutions.

Forthcoming posts

Post No 3 considers the main engine-rooms of scholarship, which are academic disciplines. I look at the tasks that pre-occupy university researchers, shape their distinctive culture, and (according to some critics) generate siloed views of the world.

Post No 4 looks at the importance of discipline-bridging processes — the main circuits by which inter-disciplinary work gets done, and some of the disciplinary potential for over-siloing gets modified.

Post No 5 then considers the endemic competition amongst researchers and scholars, and how that relates (perhaps in unstable ways) to the co-operative and collegial elements of academia.

Post No 6 considers how academic competition and collegial working both translate into the diverse career trajectories that operate within universities and disciplines.

Post No 7 finishes the series by briefly exploring modern universities as bureaucratic organizations, and showing that their ‘governance’ arrangements are perhaps not as unique as academics like to suppose.

I hope that you’ll stay tuned!

Further resources

An in-depth treatment of the themes related to this series of posts is given in Patrick Dunleavy and Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press).

You may also find useful my @Write4Research Twitter feed, which pulls together a wide range of the recent discussions relating to academic writing, university organization and academic impacts.

The open science movement has been gathering force in STEM disciplines for many years, and some of its procedural elements have been adopted also by quantitative social scientists. However, little work has yet been done on exploring how more ambitious open science principles might be deployed across both the qualitative and quantitative social science disciplines. Patrick Dunleavy sets out some initial ideas to foster a cultural shift towards open social science, explored in a current CIVICA project.

The open science (OS) agenda has grown markedly in recent years, perhaps threatening to become ‘all things to everybody’ in the most inchoate accounts of what OS means. Yet so far, despite some optimistic recent findings, OS practices have made a relatively modest impression in many social science disciplines. Perhaps this reflects OS’s overly ‘physical’ or STEM science roots. Some well-known open science websites seem to focus only on quantitative lab, experimental and computational work. Apparently excluded are even other STEM fields like ecology, where precise controls of background conditions for fieldwork are unfeasible. This pattern repeats in the social sciences, where some early handbooks and pioneer units in US universities promoting open social science ideas have focused solely on quantitative data analysis research, construed in narrow ways.

As part of a CIVICA research project funded by the EU’s Horizon Europe programme, eight major European social science universities (LSE, Sciences Po, Hertie, Bocconi, EUI, CEU, Stockholm School of Economics, and NUPSPA in Romania) have come together to try to explore more broadly the authentic academic purposes that can be fostered by adopting open social science ways of working. We aim to go beyond the bureaucratic box-ticking character of some past, limited ‘open science’ approaches, and to make progress on a more ambitious academic agenda (even if some avenues may prove difficult). This piece covers initial thoughts on eight core principles, for which we are keen to hear comments and feedback.

1. Using open access publishing

Wherever feasible, research results and analyses should be published openly, making full text analyses and associated datasets maximally accessible to other researchers, including those in nearby disciplines. In addition, it is helpful if research results are also communicated to other potential audiences using modern, digital, and accessible social media. All modern social science work deals with ‘human-dominated and human-influenced systems’ that are fast-changing and complex. In this respect, the ‘ordinary knowledge’ of participants and practitioners, potentially engaged through open publication, has considerable value for contextualizing and improving scholarship (as Lindblom and Cohen famously argued). Effective dissemination also ensures the widest possible academic scrutiny of new work, improving fact checking, problem-solving, research accuracy and the emergence of diverse scholarly voices. The growth and improvement of ‘citizen social science’ also rely heavily on maximizing open access to scholarship. Finally, the experience of using open access publishing and impact-conscious dissemination can encourage researchers to delve further into other open science approaches.

2. Making quantitative research datasets open and able to be reused

All the data supporting published quantitative research articles and books, plus details of their definitions, coding, and analyses, should be accessible — so that any of them can be easily checked if questions arise. In addition, researchers should take steps to encourage the wide re-use of their data by other analysts, conducting different kinds of studies. Most public and philanthropic grant-funders now require research data to be deposited in open archives (with well-explained documentation and data in accessible formats) once projects are completed. However, a great many corporate- or university-funded research datasets are not yet available. The growing importance of using proprietary social media data in research has further exacerbated this problem.

In other areas, the trend towards multi-national and multi-team research efforts has fostered the development of re-usable and comparable datasets covering multiple countries, or datasets that include pre-defined common questions that can be ‘pooled’ into more inclusive or authoritative resources. Achieving more improvements may entail new research taking better account of the best/strongest available research in a field (e.g., by using systematic reviews). Developing a culture of open data along these lines, would both promote and enable less silo-bound disciplinary approaches to defining questions and variables in quantitative social science.

3. Making quantitative research reproducible

The research results achieved by one team should be reproducible by other researchers using the same datasets and analysis methods (see fig.1). The endorsement of the well-known FAIR principles of data stewardship by many universities has extended this approach to cover smaller and self-funded studies. This is a wide imperative, one that goes far beyond the alleged ‘reproduceability crisis’ in some disciplines, such as psychology (often misleadingly termed a replication crisis). Many quantitative journals require a replication archive (RA) as a condition for publishing quantitative articles. Academic journals that have appointed specific Data Editors to check the quality, scope and useability of RAs have especially advanced a culture of openness.

Figure 1: The Turing Way diagram of reproducible, replicable, robust and generalizable research.

Source: The Turing Way project illustration by Scriberia. Used under a CC-BY 4.0 licence. DOI: 10.5281/zenodo.3332807. See also here.

Yet improvements in reproducing results are hard to achieve, even in the experimental STEM sciences. Transferring methods between an original team and colleagues checking reproducibility entails overcoming tacit or implicit knowledge at many stages of a project. At a micro-level progress may rely on expanding the recording and documentation of information, data and analyses undertaken across multiple experiments, models, data-runs, fieldwork expeditions or archive visits. More systematic use of journaling, lab notebooks, and documentation of searches, coding analyses etc., are also potentially important here.

4. Improving the reproducibility and re-useability of qualitative evidence

Qualitative researchers in many social science disciplines have made far less progress in creatively adopting open science practices. There are undeniably more logistical issues in making knowledge, information and data drawn from interviews, archives, documentation, text sources, images and so on easily available for scrutiny or re-use, for diverse reasons — including information made available ‘off the record’ on ‘non-attributably’; preserving the anonymity of research interviewees, patients, or those affected by problems being analysed; restrictions imposed by owner or museums on the reuse of images or scans of documents; or extensive documentary sources not being available in digital forms. We are still in the outermost foothills of exploring what open science may mean in qualitative research, and the scope of feasible changes is often contested. Yet the challenge is to find new ways of undertaking research, and new steps that can mitigate the impact of current barriers.

5. Enhancing the replicability of research

As the Turing Way diagram above illustrates graphically, it is also vitally important for the integrity and prestige of all the social sciences that research analyses and results found in one dataset or body of evidence by one team can then be replicated by other researchers using the same treatment or methods on different data sources. Although no invariant ‘natural world’ lies behind the complexities in modern social sciences, similar situations and datasets should not produce radically divergent findings when analysed using the same methods — e.g., because the range of countries, dates, or data included changes somewhat. Improvements in replicability are especially difficult in field research disciplines like ecology and the non-experimental social sciences, where complex background conditions may be shaped by hundreds of causal influences, all operating at once and changing constantly.

6. Enhancing the robustness of research

When different teams of social scientists analyse the same datasets or bodies of evidence, using different analysis methods, they should none the less generate consistent results (Fig.1). Greater ‘triangulation’ of different research approaches focused on the same phenomena can generate stronger levels of assurance that results are not artefactual. In some areas of the social sciences the pooling and sifting of published evidence has been intensively studied (as with central bank economists seeking to incorporate the widest range of trends-data into modelling the whole economy), yet divergent overall judgements often still result. Improving the robustness of economic and social analyses is key if we are alter the widespread media assumptions that STEM scientists ‘find’ results, but social scientists can only ‘argue’ for their ‘interpretation’ of results.

7. Boosting the generalizability of research

We also ideally want studies of different sets or types of evidence gathered by different teams to none the less add up to a coherent, common picture of what is going on. Cumulating social science knowledge more could make it more applicable across a greater range of social settings and time periods, and allow research findings to be calibrated and adapted with some confidence to predict outcomes across diverse settings. Greater generalizability could also boost the confidence of both researchers and practitioners/citizens that academic research provides reliable bases for action, organizational decisions, or policy-making, and that some expert consensus exists.

8. Making more use of ‘citizen social science’

Research results need to be communicated back more to the subjects, organizations and communities involved, and their reactions and understandings should be sought, assessed, and incorporated wherever feasible. The procedural steps in OSS outlined above create opportunities to keep participants informed or engaged throughout the process, rather than results only emerging months or years later with formal publication. This can be achieved via formal processes, where research informs participatory processes (as with deliberative democracy), where citizens and networks undertake some tasks themselves that feed into research, or where researchers and communities co-produce and co-steer outputs. However, taking citizen, user or practitioner feedback seriously can also be more generally practiced, in less formalized ways that none the less refine and strengthen researchers’ understandings.

Conclusions

The sociologist Randall Collins famously argued that the STEM sciences succeeded so spectacularly in the last 150 years because they developed a ‘rapid discovery /high consensus’ approach to research. The greatest scientific prestige attaches to making new findings at the research frontier, while inside or behind the frontier ‘normal science’ levels of agreement are achieved on the prevalent scientific paradigm. By contrast, social science research has achieved far less standing because of deep theoretical/ideological dissensus on what counts as fundamentals, and a relatively high turnover of evanescent findings or ‘fashions’ of analysis that have lowered its prestige. Developing open social science is a movement that could re-focus social science towards achieving more reliable advances in knowledge at the research forefront, while also hopefully growing a somewhat greater (even if probably still moderate) level of social scientific consensus on the understanding of core societal processes.

______________________

CIVICA Research brings together researchers from eight leading European universities in the social sciences to contribute knowledge and solutions to the world’s most pressing challenges. The project aims to strengthen the research & innovation pillar of the European University alliance CIVICA. CIVICA Research is co-funded by the EU’s Horizon 2020 research and innovation program.

Note: This article was first published on the LSE Impact of Social Science blog.

About the Author

Patrick Dunleavy is Emeritus Professor of Political Science and Public Policy at the London School of Economics, and the Editor in Chief at LSE Press. With Helen Porter (LSE) and CIVICA colleagues, he leads a workgroup that is compiling an open science handbook for both the quantitative and qualitative social sciences. His most recent book is Maximizing the Impacts of Academic Research (Bloomsbury Press, 2020 (originally Palgrave), co-authored with Jane Tinkler.

Patrick Dunleavy

@Write4Research and London School of Economics

With inputs from: Jane Tinkler (Nine Dots Prize), Sierra Williams (PeerJ), David Ross (Sage Open Access), Kieran Booluck (LSE Impact blog), Beth Clark (LSE Library, Head of the Digital Scholarship and Innovation Group), and Nancy Graham, (LSE Library, Research Support team head)

Executive Summary

Many current academic citation and referencing practices are out of date and dysfunctional, especially in leading only to closed-access and paywall sources, or in providing only details of ‘legacy’ print formats. The central principles of this Digital Style Guide are that

1 All citations/ references should lead wherever possible to a digital text, database, or other information source.

2. The primary source cited should wherever possible be open access — so that it is immediately available in one click to readers. Closed access and paywall sources should always be cited as well, but now in a secondary role.

3. Where an open access digital source is not available, referencing only closed access and paywall sources will have to suffice, as now. However, authors should try to provide clickable links to additional information useful to readers. We suggest economical ways of doing this.

4. Adapting to this new orientation requires some detailed but consequential changes in the items included in all citations, and in how they are triggered in texts and other outputs. We set out a modernized approach to citing, adapted to 21st century academic and scientific practice in an increasingly globalized academia.

TOPICS COVERED

A. Major issues and suggested innovations

B. Smaller suggested changes in citations procedures

C. Detailed Guide: How to cite different kinds of core academic sources

A. Major Issues and Suggested Innovations

1. Seeking to provide digital open access citations raises a number of fundamental issues which need to be tackled in a concerted way.

The rationale for open access and open science

2. The suggestions in this style guide are designed to radically and quickly improve the communication between university researchers and very large groups of readers worldwide who do not have comprehensive access to paywalled sources (such as most academic journals and books). An expensive facility like Science Direct, which allows those with very high quality access arrangements to the right journals to immediately consult any referenced sources (wherever it is located), shows the enormous potential here.

3. The main sets of people who would be helped by the far wider open access approach set out here are skilled knowledge workers:

- Researchers, teachers and graduate students in smaller or less elite universities. Worldwide we estimate that there are around 60 million people working or studying in higher education. Staff and students at around 2,500 elite or better-funded universities have excellent digital access to journal resources via their libraries. But many other institutions have only limited or very partial access to journals, and often now relatively few books beyond online textbooks.

- Teachers and students in near-university colleges and in further education systems, who number many millions but often have little access to any sources beyond textbooks.

- Executives and professional in private sector corporations — ranging from multi-national through medium sized to small firms. Business people generally have no regular or easy access to academic journals and few research books — outside small specialist staffs in major corporation R & D labs.

- Civil servants and government or public sector officials have little access to journals or academic books, and restricted budgets to acquire any more. Again there are some exceptions for small staffs in specialist R & D labs, and partial exceptions for public health care system doctors and some health professionals.

- Staff in charities, non-governmental organizations, think tanks, and many professional organizations may have small libraries of key books but generally cannot afford journal subscriptions.

- Most professionals in private practice and independent scientific research and advisory roles.

- Consultants, media intermediaries, journalists and bloggers.

4. All these groups now play essential and enduring roles in sustaining contemporary complex civilizations, and in co-producing and disseminating knowledge that is vital for academic and scientific development. Collectively some experts have suggested that these kinds of knowledge workers number at least 120 million people worldwide. The goals of ‘open science’ and the open access movement generally recognize that university researchers must work co-operatively with as many others as possible to maximize the value of scientific and academic work. Increasingly too these goals have been strongly supported by government funding agencies across the UK and the European Union, Australia and other countries; and by almost all the world’s largest philanthropic foundations. For instance, every journal article that is to count for universities in attracting research support from the UK government in its 2021 audit of research (the ‘REF’) must be available in an open access form. Paywall-only articles are disqualified from the exercise and will attract no grant funding (although there are a few exceptions).

5. In addition, systematically fostering open access can help a far wider range of people with the interests and skills relevant to scientific and academic work to stay in touch with the disciplines from which they have graduated, and to find out about new areas of knowledge advance. Key groups here are:

- independent researchers and authors working outside of a university affiliation;

- PhDers and others studying at advanced level but not full time, or not at elite institutions;

- school and college teachers; and

- people who might have liked to pursue further study or an academic career but could not for various logistical or financial reasons;

- interested alumni from your own university, especially those recently graduated, and others with particular aptitude or interest in an area of work; and

- ‘lay’ people who have many good reasons to learn about and critically assess specialist knowledge in particular areas — such as patients with particular diseases or conditions, and their families and carers; or members of the public concerned about pollution problems, environmental conservation, historical heritage preservation or cultural development and creative arts.

Huge numbers of people in all these categories constitute the ‘informed public’ whose support is crucial for the continuing development of scientific research and academic work across many different fields.

Prioritizing open access sources

6. We are still transitioning to fully open access publication, and probably will be for the next fifteen to twenty years. In this interim period, different types of sources have to be handled in somewhat different ways.

(i) The simplest case is where the full, final text is gold open access (OAg), free of charge to all readers, with no paywall. For OAg texts published in as articles in a journal and as books, this solution generates the smallest and most efficient references, with no need for duplication. Include the digital object identifier (DOI) number in a web-clickable format (i.e. http://doi.org/ followed by the DOI number). If an OAg source has no DOI, there should be a permanent URL, which can be used instead.

(ii) Where a paywall article or book has a ‘green’ open access (OA) version, the author has deposited a final manuscript version or even a proof read/edited version of the paper in a university or institutional repository, from which it can be downloaded free of charge. Here cite the green OA source first. Give the Repository Name and a permanent URL. The best institutional repositories will have their own distinctive shortened URL links (e.g. a Stanford University one looks like this: http://stanford.io/2fLBDow); or they will issue DOI numbers for all their documents; or preferably do both. In addition, the paywall version of the text is then always cited second (see examples below). The formatting here is broadly as now, except for some small changes in conventions suggested below.

(iii) For texts without a formal green OA version, the paywall or closed access version is cited first, again broadly as now. However, wherever authors know of a version of the text available on one or more widely used commercial sources — especially ResearchGate, Academia.edu or Mendeley — links to them should be cited second. These sites do not meet the ‘purist’ definition of green open access. Nor are their URL links guaranteed to be as permanent as institutional repositories. However, they are extensively used already by scientists and academics, and their value is widely appreciated by researchers and students. These sites do also provide ‘enduring URLs’, which empirically are much less likely to go out of date and be subject to ‘link rot’, and thus should stay valuable for readers over many years.

(iv) Where a paywall text Z is digitally inaccessible but does have an earlier or alternate version Y, authors should cite Y as a separate entry, and link Z to Y. Check to see if you can find a related version of the text — such as a pre-print, conference paper or working paper. Text Y may differ from the final ‘version of record’ in Z. Yet Y helps most readers by bearing a ‘close family resemblance’ to the inaccessible text, and in many cases it may be near-identical. At the end of the citation for text Z, just put: ‘See also text Y’.

(v) Finally, if none of these strategies is possible, the closed or paywall source is cited alone, again broadly as now.

Page numbers and precise quotation

7. Precision in quotation is an important scholarly virtue, enabling readers to check that a view attributed to another author has not been misquoted, manipulated or taken out of context. In the legacy print model page numbrs were the essential vehicle for achieving precision . However:

- Page numbers are already completely different in ‘early online’ versions of journal articles that are later grouped into volumes and issues for a print version — often now with a lag of up to 18 months. In a digital world these early online versions may in fact remain fully available, creating long-running and not time-limited ‘version control’ problems. (And of course, early online versions are often lodged near-permanently in Mendeley and other peer-based repositories from which they are widely available still). Some top journals have responded by shifting to ‘continuous online’ publishing, sensibly abandoning altogether the ‘print legacy’ concept of issues (with pagination defined across multiple papers).

- In digital texts page breaks can only be held the same as in print versions by using restrictive formats, like PDFs, which have many disadvantages still. Most HTML format articles are continuous and do not indicate where print page breaks occur.

8. As soon as we assign priority to open access and digital sources these already serious obsolescence problems become critical. Many important digital sources (like blogs) have no page numbers or page breaks, but can still be lengthy and substantial contributions to scholarly debate. And with other digital texts (such as books on Kindle or in ebook versions) readers themselves control the font size, and so change how pages appear and where page breaks occur.

9. We suggest that page numbers should be scrapped completely. Instead precise quotation should be realized in the following way. If author A wants to specifically cite a particular piece of author B’s work, then A must quote a minimum five or six word phrase in their main text that is distinctive to the passage being cited. A reader following the digital trail then clicks on A’s URL link to B’s text, crosses to it and from the top of B’s text uses Ctrl+F plus the quote text to find the exact passage involved.

10. In practice this means that we must completely abandon the familiar but vague style of reference where an author summarizes and cites a text, without specifically quoting from it. Without page numbers we can only cite like this:

‘Shifting functions from the government sector to off-budget bodies has been a core element in new public management (NPM) approaches (Dunleavy and Margetts, 2013)’.

But we achieve precision by instead including a findable and distinctive short quote:

‘Margetts and Dunleavy (2013) consider “externalizing services from the government sector to off-budget bodies” as a core element in new public management (NPM) approaches’.

11. Note that fixed numbering systems for exhibits — such as Figure, Table, and Box numbers — remain perfectly viable in the digital open access citation system. So too do section or paragraph numbers, often used in ‘grey literature’ reports; and numbering systems from older main texts, such as the books, chapters and verses of the Bible.

Enhancing the reproducibility and replication of research

12. In some STEM disciplines — especially medicine, psychology and bio-sciences — some recent research has suggested that the results from many peer reviewed articles published in top science journals cannot be reproduced by the same investigators using the same techniques, nor replicated by other teams. Such concerns are corrosive of the public trust in science. Other studies in the social sciences have found that research teams can rather easily make mistakes in creating, cleaning or analysing datasets.

13. In response, increasing numbers of journals in quantitative disciplines have begun to require that researchers whose articles are accepted also make available a ‘replication archive’. This should contain their key data, along with sufficient information on variables and methods to allow other users to check their methods, processes and results in detail, and if appropriate to seek to replicate them. Such enhanced replicability requirements are harder to develop in the qualitative social sciences, such as studies relying on non-attributable interviews. The issue also remains very controversial in some humanities subjects, especially perhaps for historical or literary work based on un-digitized and hard-to-access paper archives.

14. Fostering greater open access can help to improve replicability in two main ways. First, a shift to more of a ‘show and tell’ ethos might (for example) see historians depositing with their articles or books their own numerous photographs of key passages from otherwise undigitized documents. Second, the computer scientist Eric Raymond summed up the ethos of the ‘open source’ movement in software development by saying: ‘Given enough eyeballs, all bugs are shallow’. By helping more readers to immediately find more source materials in their full form, open access powerfully counteracts the risks of academics misinterpreting other authors’ work; of researchers misreading or misquoting sources such as datasets, data tables or archive entries; or of technical mistakes in analysis going unnoticed in algorithms, statistics, spreadsheets, software or other models.

15. For all qualitative work in the social sciences, the Princeton political scientist Andrew Moravscik suggested two key rules for ‘active citation’ in 2009:

‘Rigor: Any critical and contested substantive empirical point in a scholarly case study should be backed by a precise and annotated citation to one or more presumptively primary sources.

Transparency: Citations must contain a hypertext link to a reproduction or transcript of some part of the source’.

Moravcsik argues that these steps can boost the reliability of qualitative research by enhancing the quality of scholarship; encouraging wider criticism; creating richer secondary analysis and meta- analysis; and fostering greater inter-disciplinary engagement. A later 2014 piece develops his theme that ‘Transparency is the cornerstone of social science’ — especially complete clarity in what the data actually show; how analyses have been conducted; and ‘production transparency’ covering how sources were selected. Our suggestions below are strikingly consistent with this approach, and could help create some of the building blocks that Moravcsik advocates.

16. In some preliminary groundbreaking work on these ideas, it became clear that the current partial development of digitization is seen by some humanities scholars as a basis for negating any move to greater open access sourcing of historical data and documentation by researchers themselves. On this view, academics have no role to play in making sources more open via their research: we should instead wait for some future, official ‘big bang’ digitization effort to get funded. To the contrary, we believe with Moravcsik that the everyday work of scholarship can rapidly have transformative effects on the digital availability of documents and information. To take a small example from the UK government. Here documents often become inaccessible in practical terms after any change of government (when ministers and policies shift). Whitehall departments send almost all their previous materials to the National Archives, which then takes time to get them back up online, and then only in part. Yet if academics have stored their own downloaded copies of reports etc on Mendeley or other peer-store sites, these materials remain immediately available for use by scholarly communities.

What we are NOT saying

17. Earlier versions of many of the ideas here have been imperfectly expressed in blogposts, which have in turn generated very substantial volumes of Twitter commentary. Many Twitter participants have apparently responded to previous tweets they saw, but without reading the original blogposts, therefore missing some context for the ideas discussed. And scholars in some disciplines and specialisms — especially historians and archivists — have clearly reacted very adversely to some of the issues and sensitivities raised for them here.

18. So here is a list of completely false propositions that were generated in the Twitterstorm, and which we are NOT saying or advocating.

B. Smaller suggested changes in citation procedures

For all items

Give Surname, Full First Name for all authors, and optionally one more initial as well. Rationale — simply giving one initial and surname is radically insufficient to create distinctive identities in a globalized academic world.

Use semi-colons to separate out author name in long lists. Rationale — existing listing practices (using just commas and stops) assume that (Western) first names and surnames are clearly distinguishable. This is not the case with authors from many different countries and cultures.

When OA and published texts are both available, always assume that the final, formally published text is the author’s preferred version. Rationale — this will generally be the case, and in STEM sciences especially the journal paper is also the ‘version of record’. The only exception occurs if you know that the author has explicitly signalled something contrary — e.g. by putting up an OA version that is newer, revised or updated compared to the paywall version (like a ‘Director’s Cut’ of a film).

Use shortened URLs to replace any lengthy URL, especially perhaps non-permanent URLs. Rationale — For aesthetic reasons it is best to avoid long URLs, which are also liable to transcription errors, especially if there are gaps or underlines in addresses. Many long addresses (e.g. for blogposts and magazines) also repeat the title of pieces. A key disadvantage though is that if shortened URLs are wrongly transcribed, they become irrecoverable — so their resilience is low.

In addition, there are different types of shortened URLs. Short links from university repositories are clearly best for their own contents. Some academic purists criticize commercial short URLs as potentially adding to ‘link rot’ if a whole company ceases business and all its links then cease to work. Some small academic sites seek to guarantee permanent URLs. However, empirical experience suggests that perilously funded sites are in fact those most likely to cease operating. So you may be better off using a big and more viable commercial shortening site, such as at www.bitly.com, chosen here. This site is also very simple to use.

For journal articles

Never use abbreviations of journal names. Rationale — abbreviations are an absurd legacy hangover from the days when ‘hot metal’ printing was expensive, and when closed elites knew every esoteric abbreviation in their field. In the digital and OA era this past practice is completely pointless. (However, you may still have to comply with pointless formats when submitting journal articles).

Always use the full web address format for DOIs, beginning http://doi.org/ Rationale — this already forms a welcome part of APA (American Psychological Association) style guidance. Giving a DOI not as a web address is not clearly clickable and may be confusing for new students and readers. How to do it — find the DOI Number of a journal article on its opening web or printed page, and add it (with no spaces) after the prefix above — e.g. http://doi.org/10.1177/1354068811411026

For books

Give country of publication. Rationale — some multi-national publishers still run pretty separate operations in different countries — e.g. Oxford University Press in the UK/USA versus OUP in India. Knowing which country a publisher is in is also more important as we move towards a global academia.

Don’t give place of publication for publishers. Rationale — no one cares about this any more. Indeed it is now often pretty hard to find out from either books or publisher’s websites exactly which city or town publishers are located in (or which of their multiple sites is the operative ‘home’ one). All publishers are online so this is now unnecessary.

For publisher names, give enough to be distinctive or familiar, but no more. Rationale — readers only want to find the publisher, not write them a legal letter, so leave out ‘and Co’, ‘Inc’, ‘Books,’ and unnecessary parts of the legal name.

Give a working publisher’s URL for every book, even if it is not a permanent URL. Rationale — clicking through can help readers find out more about the text easily. Even if link rot later occurs, a ‘fail’ message can still help readers search for the book within the publisher’s site. How to do it — check the publisher’s website.

Give a Google Books shortened URL for every book, so long as you find that a ‘snippet view’ or better is available. Rationale — this information is partial. But it can none the less greatly help potential readers to better assess the value of the text for their distinctive needs, before incurring the costs of ordering it or looking for it in a library. For instance, a search in GB will often let you see how many times a concept, country or issue is mentioned in a book, even if many of the pages are not viewable. How to do it — check Google Books.

Signal when an e-book or digital version of an otherwise paper-only book is available in at least some libraries, using the [LEV] code explained below. Rationale — this helps potential readers to see if their library has (or can arrange) access. How to do it — include the [LEV] code if your own library holds a digital version or if you know of another library that does. [For experts: Publisher’s online catalogue pages sometimes indicate this (but not universally), as do World Cat entries].

C. Detailed Guide on How to Cite Core Academic Sources

JOURNAL ARTICLES

‘Gold’ OA journal article:

Teruya, Kenta; Oguma, Ayumi; Nishizawa, Keiko; Kamitakahara, Hiroshi; and Doh-ura, Katsumi. (2017) ‘Pyrene conjugation and spectroscopic analysis of hydroxypropyl methylcellulose compounds successfully demonstrated a local dielectric difference associated with in vivo anti-prion activity’, PLoS ONE, 21 September. [OAg] from https://doi.org/10.1371/journal.pone.0185357

Comment: ‘Gold’ open access is the ideal format for keeping citations brief and clear. Note that the full name of the journal (which is PLoS ONE) is used. The DOI has resilient features by including a journal name reference (the ‘pone’ bit). With continuous online publishing volume and issues numbers are irrelevant. However, giving the day date of publication can help readers find materials in an online mega-journal like this. Note that the authors’ use of a full narrative heading helps to clarify a complex STEM title, while also giving the key finding well.

Margetts, Helen and Dunleavy, Patrick. (2013) ‘The second wave of digital-era governance: a quasi-paradigm for government on the Web’, Philosophical Transactions of the Royal Society A, vol. 371, pp. 1–17. [OAg] from http://doi.org/10.1098/rsta.2012.0382

Comment: Another simple OAg reference. The journal’s name is spelt out in full, ignoring its own (unpredictable) convention for abbreviating (which is Phil. Trans. R. Soc. A). Again, the ‘rsta’ in the DOI identifies the source (for an expert), somewhat improving its resilience to transcription errors. No issue number is needed or possible because this journal does continuous online publication.

‘Green’ OA journal article

Chalykh, Oleg and Silantyev, Alexei. (2017) ‘KP hierarchy for the cyclic quiver’. [OA] from White Rose Research Online: http://eprints.whiterose.ac.uk/119027/

Also: Journal of Mathematical Physics, vol. 58, issue 7 (July). https://doi.org/10.1063/1.4991031 [PW].

Comment: With a ‘green’ OA journal article, a full text version is freely available (here, an accepted manuscript) and is referenced first. However, we must assume that the author’s preferred version (and ‘version of record’) is the paywall one, given second — with a [PW] warning for readers. This is published online but has an issue number also. As with most commercial journal articles, note that it is easy to make transcription errors in a numbers only DOI, and it is impenetrable if such a mistake is made.

Dunleavy, Patrick and Diwakar, Rekha. (2013) ‘Analysing multiparty competition in plurality rule elections’, LSE Research Online: http://eprints.lse.ac.uk/38452/ [OA].

And: Party Politics, vol. 19, no. 6, pp. 855–886. http://doi.org/10.1177/1354068811411026 [PW].

Comment: Here we give the date, volume, issue number, and pagination of the final 2013 paywall version — even though this exact paper was in fact fully published ‘early online’ 18 months earlier, in 2011, and of course with different pagination. Again this kind of DOI is easy to mis-transcribe.

Journal article available digitally, but not as a formal OA version

Wu, Yong; Li, Pengpeng; Zheng, Ping; Zhou, Wenjuan; Chen, Ning; and Sun, Jibin. (2015) ‘Complete genome sequence of Corynebacterium glutamicum B253, a Chinese lysine-producing strain’, Journal of Biotechnology, vol. 207, no.10 pp.10–11. https://doi.org/10.1016/j.jbiotec.2015.04.018 [PW]. See also [Non$] from ResearchGate: Wu, Yong; Sun, Jibin; and Zheng, Ping. (2015) ‘Corynebacterium glutamicum strain B253 plasmid, complete sequence’ http://bit.ly/2fDno8t

Comment: This is a short data report, so it is especially valuable to have an easily accessible, non-paywall version. The RG link is lengthy, so a shortened URL helps concision. Note that authors and title differences across the two versions have to be recorded.

Fisher, Dana R. and Green, Jessica F. (2004) ‘Understanding Disenfranchisement: Civil Society and Developing Countries’ Influence and Participation in Global Governance for Sustainable Development’, Global Environmental Politics, Vol. 4, no. 3. pp.65–84. https://doi.org/10.1162/1526380041748047 [PW]. See also [Non$] from Research Gate: http://bit.ly/2hC73Bm

Comment: Again the RG link is lengthy, so a shortened URL is used.

Journal article is paywalled but has a ‘family resemblance’ version

Günther, Isabel; Grosse, Melanie; Klasen, Stephan. (2016) ‘How to Attract an Audience at a Conference: Paper, Person or Place?’, German Economic Review, Early view: 13 September. https://doi.org/10.1111/geer.12113 [PW]. And see:

Günther, Isabel; Grosse, Melanie; Klasen, Stephan (2016) ‘How to attract an audience at a conference: Paper, person or place?’, Courant Research Centre: Poverty, Equity and Growth — Discussion Papers, №210. https://www.econstor.eu/bitstream/10419/142696/1/862719127.pdf [OA]

Comment: Both these versions seem substantively the same, as witnessed by strong title similarities. So the second cite may actually be an OA version of the first. But in cases of any doubt treating the second version as a ‘family resemblance’ piece (and giving a full second reference) is safer.

Journal article with no OA or alternate version

Ray, Shakuntala. (2016) ‘forbidden tastes: queering the palate in anglophone Indian fiction’, Feminist Review, vol. 114, no.1, pp.17–32. [PW] https://doi.org/10.1057/s41305-016-0013-z

Comment: The reference here is essentially as now. Not using capital letters at the start of the title or for the word Anglophone look like mis-spellings, but this is how this journal does things.

Holman, Rury R; Betherl, M. Angelyn; Mentz, Robert J; Thompson, Vivian P; Lokhnygina, Yuliya; Buse, John B; Chan, Juliana C; Choi, Jasmine; Gustavson, Stephanie M; Iqbal, Nayyar; Maggioni, Aldo P; Marso, Steven P; Öhman, Peter; Pagidipati, Neha J; Poulter, Neil; Ramachandran, Ambady; Zinman, Bernard; and Hernandez, Adrian F. for the EXSCEL Study Group. (2017) ‘Effects of Once-Weekly Exenatide on Cardiovascular Outcomes in Type 2 Diabetes’, New England Journal of Medicine, 377, pp. 1228–1239. [PW] https://doi.org/10.1056/NEJMoa1612917

Comment: This article has 18 authors with diverse names, so using semi-colons really helps to give a clear author list. Some journals may ask that you limit names to only 5 or 10 people. If not constrained to do so, it is worthwhile listing up to (say) 20 authors, but not more than that. This top medical journal also includes degrees in the full author list (omitted here), but still perversely abbreviates its own name (to N Engl J Med), which makes no sense at all.

Weeks, Jeffrey. (1982) ‘Foucault for Historians’, History Workshop №14 (Autumn), pp. 106–119. [PW] JSTOR stable URL: http://www.jstor.org/stable/4288433

Comment: This older article has no DOI number. But JSTOR has assigned it a stable URL, which is cited instead.

BOOKS

Gold OA Book

Scott-Brown, Sophie. (2017) The Histories of Raphael Samuel: A portrait of a people’s historian. Australia: ANU Press. 265 pages. [OAg] from https://press.anu.edu.au/node/2443/download or http://dx.doi.org/10.22459/HRS.05.2017

Comment: This book is digitally published from the outset for free OA download. Again this makes for a shorter and very clear reference, especially by using the URL for the free download page. As a world-leading OA publisher, ANU Press also assigns a DOI to all its books. But the URL here is easier to follow and so may be more resilient. The catalogue page URL (covering sales also) is longer and not included: https://press.anu.edu.au/publications/series/anu-lives-series-biography/histories-raphael-samuel

‘Green’ OA Book

National Academies of Sciences, Engineering, and Medicine. (2017) Human Genome Editing: Science, Ethics, and Governance. [OA] from https://www.ncbi.nlm.nih.gov/books/NBK447270/ Also [PW] from Washington (DC): National Academies Press. https://www.nap.edu/catalog/24623/human-genome-editing-science-ethics-and-governance [PUB]

Comment: The permanent URL here leads to a webpage that allows only section-by-section downloads in HTML format (an off-putting choice which requires over 10 downloads to get the whole document). The National Academies give no DOI number. This all seems to be designed to get people to purchase the hardback paper copy, and the [PW] links leads only to the relevant catalogue page.

Non-OA book

Dunleavy, Patrick and Carrera, Leandro. (2013) Growing the Productivity of Government Services. UK: Edward Elgar. 365 pages, [PW]. See http://bit.ly/1UYI2wM [PUB] or http://bit.ly/2qMMdS1 [GB]. Also [LEV]

Comment: Most paper academic books are still without Kindle or ebook versions, and so are essentially inaccessible outside (elite) university libraries. Yet it can still help readers to give as much extra information in one click as possible. The first URL here links to the Publisher’s website page. The second links to Google Books (when it holds a ‘snippet view’ of the book or better, as here). The [LEV] code shows that a digital library version is available in some places: university users may then search to see if it is locally accessible to them.

Non-OA paper-only book with ‘family resemblance’ version

Book cite: Dunleavy, Patrick. (1981) The Politics of Mass Housing in Britain: A Study of Corporate Power and Professional Influence in the Welfare State (UK: Clarendon Press). [LEV] See also Dunleavy (1978) next.

‘Family resemblance’ cite: Dunleavy, Patrick. (1978) The politics of high rise housing in Britain: local communities tackle mass housing (UK: Oxford University PhD thesis). [OAg] from Oxford University Research Archive: https://ora.ox.ac.uk/objects/uuid:81c699e0-4ee8-413c-a181-08a617f28d58 and from LSE Research Online: http://eprints.lse.ac.uk/82066/

Comment: Perhaps ironically, the book here has gone out of print, and so is now only accessible in libraries with a legacy copy. But the PhD thesis (on which it was 90% based) was belatedly digitized by the university involved (Oxford). So the ‘family resemblance’ OAg source is a typescript manuscript from their repository (with rather a long URL). The author has also uploaded the thesis on their current university repository, giving a second OAg reference. The core arguments of most of the text are hence digitally accessible.

EDITED BOOKS

Gold OA Edited Book

Nicolas Peterson and Anna Kenny (eds) German Ethnography in Australia. Australia: ANU Press. [OAg] from https://press.anu.edu.au/publications/series/monographs-anthropology/german-ethnography-australia or http://doi.org/10.22459/GEA.09.2017

Comment: Again ANU Press assigns a DOI to all its edited books. But the URL is easy to follow and so may be more resilient.

Green OA Edited Book

Institute of Medicine (1995) Environmental Medicine: Integrating a Missing Element into Medical Education. Pope A. M; and Rall D. P. (eds). USA: Institute of Medicine Committee on Curriculum Development in Environmental Medicine. [OA] from https://www.ncbi.nlm.nih.gov/books/NBK231988/

Also [PW] USA: The National Academies Press. https://doi.org/10.17226/4795.

Comment: The American National Academies publications often have complex authorship arrangements, so here using a corporate author is appropriate. The first names for editors cannot apparently be retrieved from any version of this older text. The green [OA] version here is on the Pub Med Bookshelf.

Non OA Edited book

Stoker, Gerry and Evans, Mark (eds) (2016) Evidence-Based Policymaking in the Social Sciences: Methods that Matter. UK: Policy Press. [PW]. See http://policypress.co.uk/evidence-based-policy-making-in-the-social-sciences [PUB]

Or http://bit.ly/2fxfk5n [GB].

Comment: Commercial publishers give deplorably little information about what is in their edited books. But the Google Books preview is useful.

CHAPTERS IN EDITED BOOKS

Gold OA Book Chapter

McCaul, Kim. (2017) ‘Clamor Schürmann’s contribution to the ethnographic record for Eyre Peninsula, South Australia ‘, in Nicolas Peterson and Anna Kenny (eds) German Ethnography in Australia. Australia: ANU Press, Ch. 3, pp. 57–78. [OAg] from http://pressfiles.anu.edu.au/downloads/press/n2618/pdf/ch03.pdf or https://doi.org/10.22459/GEA.09.2017.03

Comment: ANU Press alsoleads best practice internationally in assigning a distinctive DOI to each chapter in its edited books. But the URL is easy to follow and so may be more resilient.

Green OA Book Chapter

Ainley, Kirsten. (2017) ‘Retreat or retrenchment? An analysis of the International Criminal Court’s failure to prosecute presidents’. [OA] at: http://eprints.lse.ac.uk/71822/ (14 pages). Also [PW] in Brysk, Alison and Stohl, Michael, (eds.) Contracting Human Rights: Crisis, Accountability, and Opportunity. UK: Edward Elgar. Forthcoming.

Comment: Open access versions of chapters are often available before their paywall publication, and so may await pagination details.

Book chapter widely available digitally, but not as a formal OA version

Dunleavy, Patrick. (2016) ‘”Big data” and policy learning’, in Gerry Stoker and Mark Evans (eds) Evidence-Based Policymaking in the Social Sciences: Methods that Matter. UK: Policy Press. Ch. 8, pp. 143–67. http://policypress.co.uk/evidence-based-policy-making-in-the-social-sciences [PW]. Also [Non$] from: ResearchGate at: http://bit.ly/2yvJONB

Comment: Like most edited books from commercial publishers, this one has only a single catalogue page, which gives only the briefest (almost useless) details of chapters. Of course, none of the chapters has a DOI. The full URL for Research Gate here is ugly and likely to be mis-transcribed (https://www.researchgate.net/publication/299467976_%27Big_data%27_and_policy_learning) and so is better given as a shortened URL (see discussion above).

Book chapter with no OA, digital or alternate version

Kalska-Szostko, Beata; Rogowska, M; Pigiel; A; and Satula, Darius. (2014) Chapter 2. ‘Novel Magnetic Carbon Biocomposites’, Ch.2 in Sabu Thomas, Nandakumar Kalarikkal, A. Manuel Stephan, B. Raneesh and A. K. Haghi (eds) Advanced Nanomaterials: Synthesis, Properties, and Applications. UK: Apple Academic Press. https://doi.org/10.1201/b16966-3 [PW]. See also http://bit.ly/2wo402k [GB]. Also [LEV]

Comment: The original publisher here offers visitors to its web page a link to the Google Books preview pages, underlining the usefulness of this source for potential readers. Reissued as downloadable in its own right the chapter has its own DOI. The whole book is also available in an ebook version in some libraries.

OTHER ACADEMIC PAPERS and COMMUNICATIONS

OAg Conference paper

Chatzilygeroudis, Konstantinos; Rama, Roberto; Kaushik, Rituraj; Goepp, Dorian; Vassiliades, Vassilis; and Mouret, Jean-Baptiste. (2017) ‘Black-Box Data-efficient Policy Search for Robotics’. Paper to the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), at Vancouver: September. [OAg] from https://arxiv.org/abs/1703.07261v2 (22 July).

Comment: This conference paper is available open access on the pre-print server arXiv — again use the full web clickable version for this URL. Two dates are needed here, one for the conference, and one for the arXiv version being put up (which is itself revised from the initial March 2017 version deposited).

Ogden, Jessica; Strutt, Kristian; Keay, Simon; Earl, Graeme; and Kay, Stephen. (2010) ‘Geophysical prospection at Portus: an evaluation of an integrated approach to interpreting subsurface archaeological features’, In Proceedings of the 37th Computer Applications to Archaeology Conference (CAA, 2009). Colonial Williamsburg Foundation, pp. 1–17. [OAg] from https://eprints.soton.ac.uk/341590/ [VOR]

Comment: The authors have designated this OAg paper as the version of record. Note that Conference year is slightly earlier.

OA Conference paper

Dunleavy, Patrick and Margetts, Helen (2015) ‘Design Principles for Essentially Digital Governance’, Paper to the 111th Annual Meeting of the American Political Science Association, San Francisco, 3–6 September. 31 pages. [OAg] from LSE Research Online: http://eprints.lse.ac.uk/id/eprint/64125 , and [OA] Conference site: http://bit.ly/2fDKGem

Comment: Many conference papers are only available from the conference website, which may not stay up permanently, or even for more than a year, and where URLs may not be permanent. Here a gold open access version is cited first. But readers may also derive useful information from an enduring conference site — such as looking at other papers in the same panel.

Conference paper with only paywall access

McDermott, Steven E. (2010) ‘White’s Three Disciplines and Relative Valuation Order: Countering the Social Ignorance of Automated Data Collection and Analysis’. In: 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 9–11 August 2011, Odense, Denmark. Available http://ieeexplore.ieee.org/abstract/document/5562788/ or https://doi.org/10.1109/ASONAM.2010.16 [PW].

Comment: A professional body has kept this paper available long-term (but behind a paywall), and assigned it a DOI also. There is an entry for it on a UK university repository, but there is no full text there, so it is not worth citing.

Working paper (assume OA)

André, Paul; Schraefel, m. c; Dix, Alan; White, Ryen W; Bernstein, Michael; and Luther, Kurt (2010) ‘Designing for Schadenfreude (or, how to express well-being and see if you’re boring people)’. [OAg] from: https://eprints.soton.ac.uk/268455/ Paper to CHI 2010 Workshop on Microblogging: Atlanta, Georgia.10–15 April. 4 pages.

Comment: Working papers are treated as published to the web. This one was also presented at a workshop, and so extra information is included that may help readers.

Pre-print (assume OA)

Acharya, Anurag; Verstak, Alex; Suzuki, Helder; Henderson, Sean; Iakhiaev, Mikhail; Chiung Yu Lin, Cliff; and Shetty, Namit. (2014) ‘Rise of the Rest: The Growing Impact of Non-Elite Journals’, Research Paper, Google Inc. 9 October 2014. [OAg] from: https://arxiv.org/abs/1410.2217

Comment: This is corporate research by Google Scholar, published OA only on a leading preprint server. Note the usefulness of semi-colons in creating a completely clear, multi-national author list.

OA Stored Blogpost

Dunleavy, Patrick (2016) ‘Submitting to a journal commits you to it for six weeks to six months (or longer) — so choose your journal carefully’, LSE Impact of Social Sciences blog, 10 November. [OAg] from: http://eprints.lse.ac.uk/70293/. Original source: http://bit.ly/2jT6hjl

Comment: Blogposts are treated similarly to magazines, so we need the official blog name and the precise day date of publication. All blogposts are digital and their content starts off freely accessible. But direct links to blogposts may not be permanent. Here the post is lodged in the university’s repository, and this [OAg] version is given first. However, readers normally benefit from seeing a post within its original blog context — e.g. they can see comments on it and often precursors (as here) — so a still-live link to a blog version is also included. A shortened URL is used because blogposts often have long web addresses duplicating the post title, as here.

Blogpost (not OA stored)

McCormack, Donna. (2016) ‘Evolutionary Theory and the Humanities’, UK: Surrey English Blog, 25 January. [OA] https://blogs.surrey.ac.uk/english/2016/01/25/evolutionary-theory-and-the-humanities/

Comment: Many academic blogposts are widely available on university-run permanent URLs, without quite making it into their university repository, as here. This post also exhibits a common problem with blogs, namely pretty ‘submerged’ information on who is actually the author.

REPORTS

Gold OA Report (simple cases)

Royal Academy of Engineering (2017) Creating Cultures Where all Engineers Thrive: A unique study of inclusion across UK engineering. UK: Royal Academy of Engineering, 58 pages. [OAg] from: http://www.raeng.org.uk/publications/reports/creating-cultures-where-all-engineers-thrive

Comment: This recent report is available free from the publisher, a professional body. We have to trust that it stays that way on this URL. As with many corporate ‘grey literature’ reports no authors are identified, and even a formal date of publication is hard to find, although the year is probably correct. For any paginated report it helps readers to always indicate how long it is, so that they can distinguish substantial publications (as here) from short communications or arguments.

White Anne, and Dunleavy, Patrick. (2010) Making and Breaking Whitehall Departments: A Guide to Machinery of Government Changes. UK: Institute for Government (London) and LSE Public Policy Group), 107 pages. [OAg] from LSE Research Online: http://eprints.lse.ac.uk/27949/ Original publisher: https://www.instituteforgovernment.org.uk/sites/default/files/publications/making_and_breaking_whitehall_departments.pdf [OA]

Comment: This is a collaborative report between a think tank and an academic unit, which has been filed in a gold OA way in the university repository. So the OAg source is given first. The URL for the NGO is OA and is still working seven years on, and so is included second: it is rather long and could be shortened (see discussion earlier). Note that the NGO name is rather undistinctive so a city clarifier (London) is added, as well as country of publication. Again page length is a useful indicator of a substantial source here.

Gold OA Report (complex case)

Dunleavy, Patrick; Margetts, Helen; Tinkler, Jane; and Raraty, David. With Dorrell, David; Goldchluk, Sofia; Khan, Mohammed Khalid; Towers, Ed; Escher, Tobias; Reissfelder, Stephane; and Hinds, Liane. (2009) Department for Work and Pensions: Communicating with customers. UK: HMSO. National Audit Office Report, 40 pages. (Comptroller and Auditor General, HC 421 Session 2008–2009). [OAg] from: LSE Research Online: http://eprints.lse.ac.uk/23987/

Comment: With reports by teams, try to include all authors, even if it is a long list, or distinguishes first and second tier authors (as here). This is an official report (hence a Parliamentary papers number is included as an archival backstop). However, this report was produced by an academic team and lodged with their university depository (with the original publisher NAO’s permission), effectively creating an [OAg] document. As with many non-current government texts the report is actually no longer available online from the original publishing department (NAO), so no URL is given for that.

OTHER MATERIALS

Newspaper/ magazine OA

New York Times. (2016). ‘Events That Led to Flint’s Water Crisis’, 21 January. [OA] from: https://www.nytimes.com/interactive/2016/01/21/us/flint-lead-water-timeline.html

Comment: With some newspaper items there are no author details to give, as here. Strictly this may not meet OA standards, but the source is a major and reliably availableone.

Newspaper/ magazine, only on paywall

The Economist (2014) ‘Scotland’s referendum: Britain survives’, 19 September. [PW] https://www.economist.com/blogs/blighty/2014/09/scotlands-referendum

Comment: Again there are no author details here. Giving a paywall URL may help readers in libraries with auto-access linking.

Our future agenda for adding additional kinds of source

We are still working on ways of handling the following types of sources. We would greatly welcome format suggestions for how to cite them in ways that stress digital open access versions.

Videos

Podcasts

Datasets

Archive materials

Interviews

We also invite readers’ suggestions of other kinds of citation sources that still need to be covered here.

Readers may also find it useful to look at this blogpost dealing with the many different roles that academic references play:

Patrick Dunleavy, (2017) ‘Why are citations important in research writing?’, Writing For Research blog, 18 March.

In the modern external impacts arena, the development of effective knowledge exchange expertise will be spread across up to nine powerful and often well-funded, centrally managed units. These are

• the university library,
• its online open access repository,
• a university press,
• website and information technology services,
• the communications (press/media) division,
• a unit handling government relations or elite contacts,
• a research support division,
• fund-raising and alumni relations organizations, and
• the contract work or consultancy support service.

Not all of these are present in all universities, but most are. So the top leadership in any university directly controls substantial resources, that could be made to be key for developing its external impacts. However, in fact each of these organizations tends to have a ‘legacy’ identity or culture that in the modern period may not be very well adapted to seeking external impacts, especially in digital mode. What is most important for generating academic and external impacts is whether the unit concerned understands or sympathizes with the idea of two-way knowledge exchange, and how effectively they have recognized the efficacy of digital and social media and moved to adapt modern methods. I review each type of organization in turn:

The university library was historically concerned with paper-based books, journals and archives-preservation, and with getting students and academics to physically visit the library buildings. This orientation is a hard one for long-established libraries to leave behind, even as they have transformed into primarily digital curators. A key legacy is often librarians’ concern to maximize three priorities. First is the continuing roles of specialist librarians, whose labor intensive operations are costly to fund. Second, librarians want to preserve their purchasing budgets for buying paid-for resources (paywall journals, ebooks and paper books), which have often been whittled away by pressures from the rest of the university and rising journal costs, especially in STEM sciences. Librarians in big universities are also often committed to maintaining and adding to their established series of research journals, and reluctant to give up legacy purchasing patterns. Third, librarians often over-identify with their physical building(s) and an ethos of services to in-person users — this is their heartland ‘mission’, like flying planes is for air forces.

Especially in small and medium or less research-intensive universities, some libraries have moved over to primarily digital methods of working, with fewer staff, smaller buildings, fewer paper-based resources and more IT-intensive modes of operating. But paid-for resources are still very critical for them, since the ability to meet journal subscription costs (often now in consortia of universities) and cover ebooks needed for teaching remains the key determinant of how much the digital library can effectively substitute for more traditional modes of operating.

There are very few jobs for librarians in managing staff or student use of free-to-access resources like blogs and open access journals — that is something they can perfectly well do themselves, so long as IT services provides the right infrastructure and bandwidth to sustain large-scale access. Conservative librarians often tend to see open access resources beyond journals as not peer reviewed and unimportant in research or teaching terms. Many university libraries still do not collect even their own academics’ on-line publications, except those received via journal subscriptions. They will characteristically not collect blogposts, for instance. And they may provide no training or guidance to students or academic staff on key blogs to follow in their discipline, nor how to use social media to create an effective push-media system to keep themselves up to date at low cost. This marginalizing of the new digital scholarship paradigm is sometimes broken down in a few areas like science communication or digital humanities, where grant or external resources can fund a specialist librarian, for a time.

Many individual librarians are personal stalwarts for open access. But otherwise university libraries’ role in generating external impacts may be rather small, with little wide involvement in developing knowledge exchange activities. In extreme cases the library staff’s contribution to impacts may be confined to just its own collection initiatives with some external relevance. They will also sometimes do the purely ‘bibliographic’ or ‘bean counting’ tasks of archiving materials for publications or impact case studies, or checking their references, to be submitted to funding-linked or ranking-linked audits like the British REF or the Australian ERA (or ‘Herdic’) exercises.

Open access repositories are generally run by university libraries, but with a different ethos. They may begin to modify their parent institutions’ legacy policies somewhat, depending on the ambition of the repository. Most of them in the UK are strictly academic-audience focused, reflecting the fact that making researcher’s publications available open access is mandated if the university is to receive block grant research funding from UK governments. In Europe a looser move to open access by 2020 will probably produce similarly academic-targeted repositories. Typically these facilities have very limited impacts in boosting external impacts because they are so difficult and unattractive to use. Normally the user interface of repositories is primitive and text-only. And the internal search systems are worse than, or at best comparable to, normal (dumb) university library catalogues. Some internal search engines initially worked OK, but have subsequently crumbled into uselessness given the scale of the publications being archived. (Quick test: put in an author name and see if the archive prioritizes the stuff they actually wrote, or just serves up a random sequence of any document in there with that author name in the text somewhere).

The presentation of materials is also normally text only — devoid of images, videos or audio resources. There is no assistance to searchers, no lists of popular downloads, no advice on similar items, and so on. Repositories also routinely do not use social media nor seek to create a community of users that could support new users in looking for information. For instance, they never advise readers — ‘If you liked that, try this’, nor do they collect or communicate other users’ evaluations of items or reading advice. Overall, repositories are likely to be less salient for external impacts than getting academics to sign up for the main external sites for hosting research materials — especially ResearchGate and Academic.edu which are far better indexed and accessible to external users, and provide advice or recommendations. Along with Google Scholar Citations (GSC) they also maximize the Web visibility of researchers and departments.

An interesting questions also arises about why hundreds of universities worldwide spend money on having their repositories separately collect, edit, refresh and repost bibliographic information on their staffs’ and researchers’ publications when GSC does this task better, free. Why not just mandate your academics to have a GSC page?

A university press exists in some universities and at first sight might seem like an organization that could greatly help external impacts work. In fact, presses tend not to play a big role because they are self-financing commercial bodies. The largest and most successful university presses typically have huge ‘legacy’ paper publishing operations in books and journals. They confront all of the same problems as big private sector publishers in adapting to digital-only and to open access publishing. They are also big, commercial operations in their own right, very committed to paywall journals and to publishing overall portfolios of books that cover their costs, or (better still) help boost the net profits flowing back to their host university. Small university presses are less locked into large legacy operations, but are typically too small to make much impression even if they could operate in different ways. Only a few university presses worldwide have yet adapted to a role that could better support external impacts, including the Australian National University Press (run by its library) which has moved across to digital only and open access publishing, covering 50 books a year. Even here, however, university presses make only limited use of social media dissemination, and the operation relies a lot on recouping costs from sales to other libraries. So compared with the blizzard of research content that universities with many big blogs and better social media operations can originate, the outputs of most university presses are too small and too weakly disseminated to count. And where they are more substantial, they are generally entirely separate operations with their own operating cultures.

Website services and IT services units can have a crucial influence on external impacts, depending especially on who is running the university website, blogs and social media. If this all forms part of a single IT services department, the development of these services is often hampered by ‘legacy’ staff attitudes. These tend to prioritize the university’s administrative and transaction services IT (for recruiting students, garnering fees, running email, paying staff etc). New Web-based services are often seen as ‘less essential’, so under-funded and under-staffed, especially where they do not directly bring in money. Communications with students are still run by email, even when there is mounting evidence that students don’t read them or miss assignment dates because email is a dead medium for young people. The idea that departments or university units should use social media that students normally use to liaise with them(even as supplementary tool) is anathematized.

More modernized IT services departments still tend to view university external communications almost exclusively in terms of a fixedly attachment to running a massive conventional (synchronous) university website. Such websites require a dedicated content management system (CMS), so staff in every department and lab have to be specially recruited or trained in order to put up even a single page of new materials. The size of university web sites always expands hugely, but internal search capacities are typically weak. The site architecture of university websites rapidly becomes byzantine as ‘a thousand nettles bloom’ partly uncontrolled, while at the same time departments complain of the centralized restrictions under which they must struggle. Many webpages become ‘deserts’ with no content, and others are ‘derelict’, with content that has lapsed or gone out of date. Broken links that are not business-critical multiply largely unchecked.

Faced by new demands to run blogs as well, even modernized IT services often do not take them seriously, assigning them low priority, and resenting the need to run 24/7 servers separate from the main website. Often IT managers seem in some way affronted that academic department and lab staff without specialist IT training can run whole blogsites, using modern software like Wordpress. IT units often recommend to academic departments that they run a blog as a component part of the university website or a sub-site. In fact, this approach never works well, greatly restricting the blogs’ visibility, and requiring staff to grapple with content management systems, Even where modern blogs are technically supported at a basic level with a dedicated server, the IT services department may not have anyone good at showing blog managers how to use the many apps or add-ons for Wordpress, nor easily able to diagnose and disentangle occasional malfunctions with blog editing.

If a separate Web services department exists (often within a differently managed Communications division) the priority and support for key external impacts IT like blogs and social media can improve (see below). But then some fault lines of divided responsibilities between Web or blog services and main IT can open up.

Communications departments may still be conventional university press offices, generating paper press releases, paper newsletters and magazines, and focusing on personal contacts with journalists, broadcasters and occasionally external elites. The Comms unit here sees its main roles as public relations, generating a flow of materials that constantly ‘hype’ or put a favourable gloss on what the university has accomplished, while also providing advice and help to university leaders to ‘fire fight’ any public criticisms, gaffes or other problems that may surface. (This last orientation is often supported by nervous top leaders who run scared of things going wrong). Normally an old-style Comms unit like this will still marginalize web-based knowledge exchange, even if they also run the Web site. A key ‘tell’ for this legacy orientation is that the press office sends university leaders daily ‘press cuttings’ or weekly details of press and broadcast coverage, but make little or no mention of social media performance or coverage.

At the other extreme a few top Comms divisions have now migrated to a fully ‘digital-first’ approach, offering researchers help with the integrated production of digital press releases, plus accompanying tweets, Facebook posts, and posts on major blogs. A key ‘tell’ for such a unit is that it offers extended social media support and training to academic departments, and the unit staff are all up to speed with the latest social media trends. They fully take on board the concept of two-way knowledge-exchange as a key aspect of contemporary universities’ pubic engagement with students, alumni and external donors.

Most university Comms units probably fall somewhere between these two poles. Typically they still have relatively more staff doing historic or inherited activities with long-sanctioned core funding, like generating non-digital (hype) press releases or magazines and supporting public events. If the main university Website is managed from Comms this too forms part of the non-controversial blocks of work. Meanwhile a minority of (overworked) staff try to support newer blogging, social media and knowledge-exchange activities. They periodically have to battle to get some time-limited or conditional funding and university support for the area. In committees they often must additionally fight off criticisms from traditionalist academics or those academics coming in new to senior university roles.

Government relations offices or elite public affairs units are often separate and powerful bodies in bigger or well-connected universities. In smaller universities this role may be filled by one or more staff who form part of the top leaders’ personal office. The role involves handling top relations with national or state politicians, university dignitaries (such as members of governing boards or councils), corporate relations around large initiatives, top professional bodies, and sometimes major philanthropic bodies or large external donors. Such units always work closely with the university president or vice-chancellor, much of whose timetable is spent on engagements with these kinds of targets. Their activities always stress ‘offline’ personal contacting, and their influence is often to minimize top leaders’ digital and public impacts activities. Instead they encourage top leaders to devote their scarce time and funding overwhelmingly to ‘behind the scenes’ and elite-level contacting activities. These units’ influence often means that university leaders are both digitally invisible to a wider public, and also get quite cut off from what academic departments and labs in their university are actually doing — except as seen through ‘hype’ press releases and ‘showcase’ fund-seeking events, a potent route for misinformation.

Research support divisions in large universities can be very powerful and sophisticated operations. The role involves constant horizon-scanning for opportunities from government funding bodies or philanthropic foundations; alerting academic departments to opportunities; helping them draw up grant bids; concerting innovative bid teams; and the dense mechanics of getting forms filled in correctly and on time. This unit may also help university leaders resolve frequent conflicts of interest: How many bids can we feasibly submit to a given funding call? How do we choose between bid A with funding g and chance of success x, versus bid B with funding h and chance y? These units play an additional key role in relation to any external audits of research, like the UK’s REF or Australia’s ERA processes. They brief leaders and academic staff on the process requirement, oversee preparations, help departments and labs fine-tune their strategies, and advise top leaders on university policies, e.g. in the UK’s REF process, who get submitted as a ‘research active’ academic, and who does not.

Research divisions vary a great deal in their orientations to impacts. The older-style, legacy departments are often like traditionalist academics in only valuing either (i) government or foundation research grants on uber-academic topics, that lead to articles in top-cited journals; or (ii) large endowment funding from corporations or private donors that allows the university to set up new initiatives, centres, institutes or labs (that will then produce more articles in top-cited journals). A hallmark of such units is that they constantly monitor how their university is scoring on numerous university rankings and research rankings. However, they are often fatalistic about the visibility of their university’s research, and they rarely have any positive strategies for improving it.

More modernized research funding units, and those with corporate relations as part of their remit, pay more attention to external impacts. In the UK, where a minimum of 25 per cent of government research block grant funding (plus around another 5% under the ‘research environment’ heading) is now allocated for impacts case studies, research divisions normally have to help academic departments plan and write up cases. It can be big business now — with a 4* impact case perhaps worth as much as 1 million pounds extra grant to a UK university in 2021–26. Universities where corporate relations and external consultancy or company linkages are big business tend to hive these functions off to separate units. Alternatively corporate relations (with businesses, government agencies and big NGOs) may be located with alumni relations in an external fund-raising division. So even in large, modernized universities, the research divisions tend to be rather conservative on, or poorly informed about, generating external impacts.

Fund-raising/alumni relations departments are very influential in all American universities (where private philanthropy is bigger in scale) and in the relatively few big European universities that have pluralized their research funding sources away from dependence on government funding. The most developed fund raiser units focus only on garnering large donations, and stress personal cultivation of very wealthy individuals or foundations. They are only interested in aspects of external impacts work that may help them hook such a donor, leading to them endowing a chair, a whole new centre (ideally with a building) or a big research program. Like governmental relations/public affairs units their own activities are characteristically digitally invisible. They also hive off mundane fund raising to departments or individual academics themselves, or to alumni relations staff, while insisting that key donor ‘targets’ are off limits to anyone but themselves.

Traditional alumni departments are also orientated to linking to former students via older-style communications media (such as paper magazines), reunion events and postal or email funding appeals, seeking smaller contributions that fuel the university’s general endowment. They tend to be more interested in convincing alums that the university is pursuing public interest goals, and so also orientated to pure research, than in external impact linkages. They have almost never used crowd-funding or kickstarter approaches amongst alumni to generate financing for particular research or impact projects. Often such units are also very orientated to developing the whole-university brand. So they not so keen on departments having sub-brands of their own, nor maintaining their own direct relations with their alums, since both might impede the flow of support to university-wide funds. All in all, they tend to have a culture that is indifferent to, and may even be hostile about, departments’ and labs’ efforts to grow external knowledge exchange.

By contrast, modernized alumni operations are far more digitally orientated. All alumni units know that a key determinant of fund-raising is whether alums value (or can be persuaded to value) a continued relationship with their university after graduation, to feel involved with its ongoing research and teaching work, to have contact with current students, to be sympathetic to the university’s pro bono activities, and to want to help advance its positive reputation. Digital communication with alumni is far cheaper and can be differentiated and targeted far more than paper-based media, especially where it is based on ‘big data’ analytics (and generates more information for such efforts). If alumni see regular blogs attuned to their current professional and personal interests, they are more likely to feel that their university is doing relevant research and impact work. And perhaps if alums themselves are asked to write blogposts, book reviews or comments on areas where they have expertise, or to advise current students on career issues in person or via Skype or Facetime, then they will be more likely to feel valued by their alma mater.

Internal consultancy and business development units are the last part of central university administrations to consider here. They help departments and researchers to do contract work with external clients, especially applied research and staff training. One key set of roles involves making contract-activities easier via horizon-scanning for opportunities; alerting suitable academics and helping them to make contacts; providing indemnity insurance and university branding; allowing research and teaching staff to be recruited on flexible and shorter term contracts than normal; administering contracts with clients; and collecting a percentage share of the overall contract price for the use of universities facilities and offices. A second set of intellectual property rights (IPR) functions is important in STEM science departments, where university research may lead to patents or licenses that are revenue-generating over the short or long term. These roles all sound as if they should strongly help external impacts, and they may well do so, especially where the central unit makes it much easier for individual academics or departments to manage their involvement with external clients.

But there are also some potential barriers here, chief of which is that the central unit is normally required to be self-financing and to return a certain ratio of profits to the university. This can produce a short-termist focus in consultancy offices, a tendency to focus on blocks of work that are easy to get and maintain. Ideally they chase repeat or routine work of a relatively undemanding kind; or incremental IPR gains of a familiar type (like patents or licensable artefacts/techniques) that can be confined to the university alone. These more mundane activities deliver regular returns and reliable contributions to the consultancy team’s high overheads, with none of the risks of people doing research on new topics or making relations with new clients. So these units are often less keen on the expense of cultivating new contacts (who might or might not bite), or promoting to clients innovative or experimental projects, that are likely to be one-off pieces of work or involve areas that seems remote from commercialization or securing future IP (intellectual property) rights. Smaller university units may go for decades without ever making any investments in ‘risky’ start-ups, or taking any equity stakes.

However, the biggest universities also have central units with a third, macro-level string to their bow, namely encouraging researchers to develop partnership or ‘star-burst’ companies. Here the university retains an equity stake or other linkage, especially in the STEM sciences in fields like life sciences or software engineering. University environments and decision processes are perhaps ill-adapted to contributing to rapidly changing industrial fields and commercial markets, where first movers reap key advantages. The university (and department) interest is in persuading researchers to move forefront work into companies with a university involvement. Or if they move into completely private firms (funded by venture capital) the interest is to maintain good and close relations between the firm founders and their originating academic department (see pages above).

The whole area around research-lead entrepreneurship by university researchers is difficult to manage, especially where the future prospects from boosting equity stake values are potentially large but also very uncertain. Some universities use a portfolio approach like that of venture capital firms (where some investments are big hits, and others just cover costs). This can generate large external impacts from some kinds of STEM research. The opportunities for such effects are more limited in less fast moving STEM science areas, and generally small or non-existent in the social sciences and humanities. In terms of both university and external politics this discipline-selectiveness is a constraint. Top leaders cannot normally afford to have their university’s development become too lop-sided, or seemingly corporate-sponsored or corporate-directed.

Overall, the fragmentation across these nine units is a key barrier to digital change within universities, however active its researchers and academics may be in promoting new modes of digital scholarship. Dozens of connected digital shifts are taking place at once, and these legacy organizational structures mostly cross-cut or inhibit them. Top university hierarchs are not well placed to realize that they have problems, partly because ‘power makes stupid’ as Nietzsche said. Leaders pay most attention to the people they meet in person, senior folk with big budgets and out of date paradigms. But digital change is (always) being built by young researchers and teachers in their own ways, mainly using resources that the university ‘standard desktop’ won’t include for another ten years.

Further resources

How to build out the digital footprint of universities’ work is discussed in more depth in my book with Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press), Chapters 7and 8.

And my @Write4Research Twitter feed pulls together a wide range of the latest writing and impacts advice.

For other related content, see the LSE Impact blog.

There are sharply divided views about the academic value and role of chapters in books across disciplines, and within some of them between defenders and critics of the form. In some humanities and social science disciplines chapters account for large shares of outputs and are still well regarded. Here ‘a book chapter.. is an independent article with roughly the same status as a journal article. The review and revision process involved is very similar to that for journal articles’ says the historians’ guide by Iacovetta and Ladd-Taylor.

My chart below is taken from Bastow et al, The Impacts of the Social Sciences, and records cites from multiple different sources for a sample of British academics in 2010-13. Chapters in books accounted for more than one in eight cites in five disciplines (sociology, media studies, history, geography and law), and nearly a quarter of citations in philosophy. Note that the patterns of chapter citing are not closely correlated with those for book and edited book citing. (Sadly this study did not cover wider humanities fields, where chapters play a big role also in English, literature studies, theology and other areas).

Chart 1: The proportion of cites going to chapters in books across 12 UK disciplines in 2010-13

In pre-digital times up until the late 1980s, chapters were well used and well respected as a form of publication in the social sciences and humanities. This was a period when academic books mostly had to be physically handled by customers (in bookshops, at conferences or via inspection copies) in order to achieve sales.

However, in the early decade and a half of the digital era, chapters in edited books became less and less easy to learn about or find. The proprietary bibliometrics systems created in the 1980s, like the Web of Knowledge and Scopus, covered only journal articles until around 2010. They ignored all forms of books and book chapters, because they were seen as unimportant for research in their heartland STEM disciplines. And although Web space costs nothing, publishers publicized edited books only with digital facsimiles of their print catalogue entries. So even publisher web pages for edited books typically did not fully list all chapter authors and their titles — a legacy practice that continues completely unchanged to this day. Chapters literally became invisible and unfindable.

The key problems with chapters

At the end of this stage, in 2012, the eminent psychologist Dorothy Bishop looked systematically across her own outputs and concluded that on average (and controlling for time since publication) the citations for her chapters in books were a third of those for her journal articles. They were also cited less than review articles (those not reporting primary research findings), with which chapters are perhaps more comparable.

She concluded that ‘There are three things that determine if a paper gets noticed:’

(i) ‘It needs to be well-written and interesting’, both factors that the author can fully control.

(ii) ‘It needs to be tagged so that it will be found on a computer search’. Many authors remain pretty ignorant of just how little publicity any publisher will give to individual chapters or their authors. Some specially salient edited books may get their own leaflets, giving complete authors plus chapter lists. These can be available a conferences, circulated in print form via libraries and professional associations, and publicized through mailing lists and email alerts. But even now (when digital space is costless) publishers’ catalogues rarely give complete titles and author or chapters lists for the bulk of edited books. So potential readers generally had no way of knowing in detail what particular chapters cover or argue, even by accessing publishers’ websites. Almost their only chance of learning more was if a free chapter is available, or if they can physically handle the book in a bookshop or at a conference.

(iii) ‘It needs to be accessible and not locked behind a paywall’. Journals are increasingly restricted on their ‘embargo periods’, the length of time that they can bar authors from re-posting manuscript versions of their paper on sites beyond their home university repository (where they can be lodged immediately). And Bjorn Brems recently estimated that 40% of new journal articles are now open access. But publishers of edited books have been under far less pressure and so they are typically opaque about their embargo periods, making open access versions harder to find.

Summing up these substantial barriers Bishop argued: ‘If you write a chapter for an edited book, you might as well write the paper and then bury it in a hole in the ground’.

On a scholarly press industry website the commentator Kent Anderson promptly added four more discouraging factors:

(iv) ‘Books aren’t as available online as journal articles because.. they remain in a packaging shell, with chapters trapped therein. There is no “chapter economy.” This limits [edited] book[s’] metadata and searchability to often the shell components and not the muscle and sinew — aka, the chapters’. Symptomatic of this problem is that book chapters are still not issued DOIs (digital object identifiers), unlike articles.

(v) ‘Journals are broadcast on a regular basis, books are not… Journal brands are more predictable, constant, and “in your face”… Regular publication means bigger journal metadata footprints. Books come out sporadically, with a changing cast of characters — topics, editors, authors, titles, subjects’.

(vi) ‘New information … contained in most scientific (empirical) articles draws media coverage.., and high interest from the most passionate researchers and practitioners in the field. This magnetic pull also draws these same influential sources of awareness-building into the review articles..’. Chapters in edited books lack these focusing supports.

Meanwhile on another front, chapters in books suffered a loss of credibility in official research audit exercises like the UK’s REF and Australia’s ERA. To the rushed academic readers on government grading panels (e.g. claiming to individually rate some 202,000 research outputs for quality in the UK’s 2014 review), chapters in books were just too hard to assess. They smacked of an effort to evade peer review — by authors publishing with their mates instead of going through the rough and tumble of journal submissions. Again this attitude in time spilled over into how (elite) university promotion committees rated outputs. Outside the book-and-chapter loving disciplines (history, English, literature studies and philosophy) ambitious ECRs and PhDs were warned off writing chapters and urged to focus on journal articles alone. The lure of writing chapters in friends’ books still remained strong for older researchers in some mixed disciplines, and for academics approached by keen publishers.

Strategies to counter past problems with chapters

These issues were serious ones, in their day. But in modern academia, and given current more favourable digital trends, their salience can be greatly reduced by using six key strategies:

A. Writing a chapter for an edited book can be a lot quicker and more predictable than hacking through journal processes. The citing process for a chapter can also get started faster if you can digitally disseminate knowledge of it as soon as it is accepted (Thompson, 2012).

B. There is generally then a gap of six or seven months before the final printed version is published in the book. Authors are now generally free to put the manuscript version of their chapters up on scholarly communication sites like ResearchGate and Academia.edu in this period, as well as lodging it permanently on their university repository. It is important to make sure that the full details of the chapter within the edited book and its editors and publishers are prominently given at the top of a chapter PDF. This helps appease publishers and editors with advance publicity gained from tweeting and FBing it out. It also means that readers can correctly reference the final text in a stable way (although they may need to recheck page numbers).

C. To generate some traffic for a piece authors can also ask the editors and publisher if theirs can be one of the free sample chapters whose final versions are made freely available so as to help advertise the book.

D. Once the book is published, and enters its key sale period, the author of every chapter (including the editors) should each write a blogpost about their own chapter, and if possible get it into a large-audience multi-author blog, just as they should do for every new journal article. Tweeting and FBing the key messages then leads readers to the blogpost, and from there there are URL links both to the print book and to the open access full text.

E. For the first year to 18 months authors that the book is on sale (or whatever the embargo period is) authors may then have to temporarily take offline the ResearchGate or Academia versions of their chapter — but of course can keep up their home repository version. However, it is also worth seeing if your editors or publisher really care if you keep these OA versions up — given that your chapter is normally not directly or separately identifiable within any aspect of the book’s publicity.

F. Once the embargo clears, authors should reinstate both the easier access OA versions, and then retweet and re-FB the chapter’s wider OA appearance.

These six steps can make sure that one or more OA-versions of your chapter are always available, so that it becomes an individually accessible unit in its own right.

Yet will publishers or editors not object to this? Sadly, there may be cases where rather ignorant publishers or old-fashioned book editors view these steps as tending to reduce the sales of the book. In fact nothing can be further from the truth. Building up usage of an OA version of chapter can help the edited book that it sits within to build up sales, credibility, recommendations and teaching uses. Especially in the critical initial sales period this encourages libraries to buy the book. The OA availability steps above might just conceivably head off one or two sales of an expensive academic volume to other academics. But they will have far greater efficacy than publishers’ patently inadequate print-era legacy strategies in boosting knowledge and institutional sales of any edited book.

The six strategies above also chime in with the growth of ‘long tail’ book retailing plus the advent of hugely better search engines. Both have been good news for the ‘findability’ of chapters in edited books. So too was the launch and rapid ascendency of Google Scholar, which covers book chapters on much the same basis as articles. Where Google Books also allows generous views into the text of edited books, and a capacity to search for key words throughout an edited book (again the publisher’s decision), readers’ access to information about chapters is also far greater now than before.

Designing chapters

As for the design and writing of chapters, all the advice given in another of my posts on creating better and more interesting journal articles applies here with equal force. Try to write a full narrative title giving the core message of the chapter. If this seems too difficult, at least ensure that your chapter title has strong narrative cues within it to the argument or conclusions. Strictly avoid formal, vacuous or ‘box’ titles that will cause your chapter to get lost in search engines. And remember there are usually no abstracts in edited books, so clear and informative titles are especially important in attracting readers. (In your OA manuscript version it is a great idea to also include a chapter abstract, even though that does not make it into the final published version).

Try to achieve a high impact start for a chapter, one that is uncluttered and introduces readers quickly to its structure. With no chapter abstract in the published version, you need an introduction that gives a swift précis of the argument before diving into the main substantive sections. It is vital to stick within the editors’ word limits for chapters, generally 8,000 to 10,000 words, which implies perhaps only four or five main sub-headings. Leave enough space to ‘close out’ your chapter by first recapping on key findings and arguments and then linking outwards to other chapters in the book (assuming that you get sight of them in time).

Conclusion

None of this is to deny that if you have strong primary research to report it is better to push it out in journals wherever feasible. But book chapters can have valuable exploratory, discursive, synoptic and review roles. And they can carry new findings too, especially in start-up fields and with good editors and editing. The old problems from the early digital phase, when for a while chapter texts became literally unfindable, and authors passively left things to publishers to promote their work, no longer apply with much of their previous force. However conservative your editors and publishers may be, you can get your chapter noticed, read and cited in the communities that matter to you.

Further resources

Producing and structuring papers is discussed in more depth in my book with Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press), Chapters 3 and 4.

You may also find useful some of Patrick Dunleavy, ‘Authoring a PhD’ (originally Palgrave, 2003, now Bloomsbury Press) which covers becoming a better author, stylist and self-editor.

And my @Write4Research Twitter feed pulls together a wide range of the latest writing advice.

Academic work is inherently cumulative — and often in tracing the evolution of ideas, methods or evidence an author or research team should cite their own previous work, especially in fields where most work tackles distinctive or applied problems (not widely studied), or follows a particular method not yet widely shared. Yet some commentators suggest that self-citations are problematic or illegitimate and argue that they should not count at all or count less than normal citations. Such critics see self-citation as ‘blowing your own trumpet’. Official bodies often exclude them from cites counts, as if they were somehow corrupt inclusions when measuring academic performance. Some bibliometric scholars concur in excluding self-citations comparative analyses of the research performance of individuals, departments and universities. And indeed there is evidence that self-citations are not as important as citations from other academics in determining how far an academic is an authority within a field . Some producers of bibliometric indicators have also begun to publish the proportion of self-citations, so as to show the number of citations from other authors.

However, there are also good grounds for recognizing that self-citations by individuals and research teams can be a perfectly legitimate and relevant aspect of disciplinary practices in different parts of academia. Figure 4.7 shows large, systematic differences between discipline groups. In engineering sciences two out of five cites are self-cites, ranging down to a fifth for medical and life sciences. In most scientific and STEM disciplines the rate is generally around a third. The social sciences and the humanities generally have low rates with a fifth to a quarter of citations being self-cites, but political science and economics approximate the lowest scores in Figure 1, whereas psychology and education are higher. In the humanities, rates of self-citation are also around a fifth, but language and communication studies use self-citation more frequently.

Figure 1: Self-citation rates across groups of disciplines

Source: Centre for Science and Technology Studies (2007).

Do these patterns reflect solely different disciplinary propensities to blow your own trumpet? It seems very unlikely. Rather this variation seems likely to be shaped by the proportion of applied work undertaken in the discipline, and the serial developmental nature of this work. Many engineering departments specialize in particular sub-fields and grow the knowledge frontier outwards in their chosen areas very intensively, perhaps with relatively few rivals or competitors internationally. Consequently if they are to reference their research appropriately, so that others can check methodologies and follow up effects in replicable ways, engineering authors must include more self-cites, indeed up to twice as many as in some other disciplines. In applied research areas many of these references will also be to reports or other ‘grey literature’, again for wholly legitimate reasons.

Similarly quite a lot of scientific work depends on progress made in the same lab or undertaken by the same author. In these areas normatively excluding self-cites would be severely counter-productive for academic development. And doing so in bibliometrics counts is liable to give a severely misleading impression. In this view the lower levels of self-cites in the humanities and social sciences may simply reflect a lower propensity to publish applied work in scholarly journals, or to undertake serial applied work in the first place.

The low proportion of self-cites in medicine (arguably a mostly applied field) needs a different explanation, however. It may reflect the importance of medical findings being validated across research teams and across countries (key for drug approvals, for instance). It may also be an effect of the extensive accumulation of results produced by very short medical articles (all limited to 3,000 words) and the profession’s insistence on very full referencing of literatures, producing more citations per (short) article than any other discipline.

There are some large gender differences amongst researchers, with men citing their own publications at a far higher rate than do women . Our current state of knowledge does not yet fully control for discipline differences between men and women academic authors, and for men in some fields being more senior on average than women. None the less, it seems that women may be somewhat under-playing links between their current and previous work, perhaps from a misplaced sense of diffidence. Or men may indeed be more boastful or self-referential?

Self-citation also tends to grow with age. Older researchers may do more self-citing, not because they are vainer, but because they are more experienced and can legitimately draw more on their own earlier work than new researchers. In some disciplines too, older academics may do more applied work than younger staff focusing on PhDs or post docs — generating the same reasons to cite their own corpus of work as those found in engineering — namely that their work draws a lot on reports, working papers for external clients, or detailed case studies that may not be easy to publish in journals.

So how should you play self-citations in your own work? It seems prudent for researchers to keep their own self-citation rate slightly below the average for their particular discipline. But it is equally not a good idea to ‘unnaturally’ suppress referencing of your own publications portfolio - because of multiplier effects where citing one’s own earlier work tends to encourage other people to cite it as well. After controlling for different factors, some research found that each additional self-citation increases the number of citations from others by about one citation after one year, and by about three after five years. Other scholars have also found that self-citations can increase the wider visibility of author A’s work. One possible logic here is that reader B doing a literature review sees Author A in her best-known work Z include a citation to some of her lesser known research. If B is conscientious she may follow up and also cite A’s lesser known work, as well as Z. (However, citing less well-known works may not often help A to grow her h score).

For senior academics, citing their own applied research outputs (such as research reports, client reports, news articles, blog posts etc.) makes sense because such outputs are often missed in standard academic databases and sources. Young researchers, with smaller portfolios of publications to draw on, need to handle self-citations carefully. They can be legitimately used to get visibility for supportive works not yet journal-published (such as working papers, research reports, or developed papers under review etc.) or for data sets.

Summing up: 1. Self-cites must only ever be used where they are genuinely useful and fully relevant for the articles in which they are included. 2. Try to ensure that the rate at which you self-cite is somewhat below the norm for your discipline group.

Further resources

How citations work is discussed in more depth in my book with Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press), Chapter 1.

You may also find useful some of Patrick Dunleavy, ‘Authoring a PhD’ (originally Palgrave, 2003, now Bloomsbury Press) which covers becoming a better author, stylist and self-editor.

And my @Write4Research Twitter feed pulls together a wide range of the latest writing advice.

The sociologist Robert Merton wrote perceptively about citations:

[T]he institutionalized practice of citations and references in the sphere of learning is not a trivial matter. [Readers] located outside the domain of science and scholarship may regard the lowly footnote or the remote endnote or the bibliographic parenthesis as a dispensable nuisance .. [But] these are in truth central to the [academic] incentive system and an underlying sense of distributive justice, that do much to energize the advancement of knowledge

Yet the significance of citations goes far beyond energizing and rewarding scientific and academic competition, and for PhDers and early career researchers it is worth briefly enumerating these rationales somewhat more.

All academic research and argument has seven essential characteristics. It is formally stated. Each work contributes to an advanced and specialist conversation. And academic work tackles difficult issues. It forms part of a cumulative and collegial endeavour. Research is evidence-based, and its provenance can always be checked. Research is also demanding and consistent in assessing empirical ‘facts’. All these features mean that referencing and citing are vital components of academic practice. The decisions that scientists and academics make about including or not including citations to support their arguments play a very important role in conditioning how their colleagues regard and evaluate their work. The Figure below unpacks a bit further the reasons why citations are so important, set against the seven criteria mentioned above.

Better appreciating the multiple roles of citations should help authors in discipline groups where chronic under-citation is a curiously seductive and hard-to-eradicate form of academic self-harm — the humanities (especially) and many social sciences. It is simply unacceptable scientific or academic behaviour now to ignore immediately relevant research or argument already in the public domain just because it does not help your case, or suit your style of work, or comes from a different discipline.

In the digital era the argument above also makes clear that open access sources should always be the primary reference sources, relegating paywalled sources to secondary status. Linking to OA texts whenever available is consistent with the scientific and academic mission, whereas referencing only paywalled sources is clearly restrictive. Perhaps, as the years pass by, even the authors of the badly out of date style guides still being issued by professional bodies like the APA and MLA will begin to take note.

Further resources

How citations work and how to track them are discussed in more depth in my book with Jane Tinkler, Maximizing the Impacts of Academic Research: How to grow the influence, practical application and public knowledge of science and scholarship (originally Macmillan, 2021, now Bloomsbury Press), Chapters 1 and 2.

You may also find useful some of Patrick Dunleavy, ‘Authoring a PhD’ (originally Palgrave, 2003, now Bloomsbury Press) which covers becoming a better author, stylist and self-editor.

And my @Write4Research Twitter feed pulls together a wide range of the latest writing advice.

To help keep up to date, please see my Twitter account @Write4Research and the many commentators on the LSE’s Impact blog