Course, force and discourse of the neoliberal university
The actual openness movement began to conquer the Organization for Economic Co-operation and Development (OECD) world as recently as a decade ago. At that time, however, neoliberalism as an economic and political concept already dominated the world. The central assumptions on which neoliberal ideology is based are the idea of people as self-interested individuals and the notions of self-regulating markets, free trade, and rules of law (for a summary, see Harvey, 2005; Olssen and Peters, 2007). This ideology, in the situation of a deepening crisis of so-called ‘welfare capitalism’, has been the basis for radical changes in the political economy of capitalism since the end of the 1980s, consisting of privatization, deregulation, financialization, and globalization (Lippit, 2010; Radice, 2013). The political philosophy that gave meaning to all these changes was based on the new, neoliberal theory of democracy, which imposed the neoclassical economic concept in areas of social life previously reserved for politics (Mirowski, 2011). Equally, the notion of ‘government’ was based on self-governed individuals, and the very concept of freedom was reduced to economic freedom within the framework of the market (Mirowski, 2011, pp.29–31). The immediate consequence of these changes was the creation of a new social order that increased the polarization of the minority, who had ever greater social power and economic wealth on the one hand, and the growing number of workers on the margins of the labor market, characterized by insecure work and social isolation, on the other (Castel, 2000; Duménil and Lévy, 2005; MacGregor, 2005).
Neoliberalism, however, is more than an economic and political ideology that seeks to diminish the role of the state in regulating the economy and to establish the political reconstitution of the society. Neoliberalism also creates a new relationship between power and knowledge that results in new strategies of power use and new technologies of governance (Rose, 1998, 1999; Ong, 2006). The view of a knowledge society is increasingly being replaced with the idea of a knowledge economy (Holmwood, 2013a). Instead of being used for public good, knowledge is increasingly becoming a mere commodity that can be bought and sold, and whose value is equal to its market value. New notions, such as knowledge management (the creation, utilization, and protection of knowledge as goods or resources by a corporate business) or knowledge policy (promoting the knowledge economy and global competitiveness) have become part of the vocabulary of policy makers and corporate leaders. The philosophy behind this postulates that the market is far superior at processing information about the world we live in than any individual, social institution, or even science. In that sense, the commercialization of knowledge represents a significant step forward in the progress of civilization (Mirowski, 2012).
To this end, higher education is now at the center of the neoliberal revolution. On the one hand, the traditional university is increasingly losing its public status and autonomy (Peters, 2013). Likewise, it has also lost the character of an institution whose mission is to reduce social inequality, injustice, and poverty. Instead, the new, neoliberal university has become not only a major generator of inequality in society, but also an institution with greater inequality among its employees than any other public institution (Holmwood, 2013b). This claim applies to higher education in the UK, but the situation seems to be no better in other countries. In the USA, it is estimated that up to 70% of university employees work without permanent employment contracts (DiGiacomo, 2005; Shore, 2010). In Sweden, this percentage is admittedly smaller at just over 30%, but these figures do not include the most vulnerable groups, such as PhD students and teaching staff without PhDs (UKÄ, 2015). At the same time, these figures include neither an enormous rise in workload nor a worsening of working conditions over the past 15 years (Kirsebom, 2016; Kniivilä, 2016).
Although the erosion of university autonomy had already begun in the 1970s (for the UK, see Radice, 2013; for Sweden, Ahlbäck-Öberg and Sundberg, 2016), the definitive establishment of the neoliberal ideology and practices took place during the 1990s, alongside the introduction of the so-called ‘new public management’ (NPM) concept of organization (Barry et al., 2001). The basic features of this concept were the replacement of traditional professional and collegial management with executive line management, a focus on performance measured by quantitative parameters, and the use of financial incentives (Donoghue, 2009, 2015; Radice, 2013; Ahlbäck-Öberg and Sundberg, 2016). Consequently, this resulted in a significant reduction in the professional and academic freedom and autonomy that have traditionally characterized higher education (Olssen and Peters, 2007).
At the same time, another key development began to affect higher education: the rise of the ‘audit culture’, characterized by measurement, performativity, and surveillance (Power, 1999; Strathern, 2000; Shore, 2010). Systematically imposed by the state and state institutions, audit culture is defined as the ‘…process by which the principles and techniques of accountancy and financial management are applied to the governance of the people and organisations’ (Shore and Wright, 2015, p.24). A newspeak, consisting of a growing number of new notions such as ‘performance,’ ‘quality assurance,’ ‘accountability,’ ‘responsibility,’ ‘transparency,’ ‘efficiency,’ and ‘good practice,’ has become an integral part of everyday life in higher education (Shore and Wright, 2015). This is experienced on a personal level by academics, and is summarized illustratively by Stephen Ball (2012. p.19): ‘Within the rigours and disciplines of performativity we are required to spend increasing amounts of our time in making ourselves accountable, reporting on what we do rather than doing it… As a consequence we become transparent but empty, unrecognizable to ourselves.’ As this quotation suggests, these radical changes appear to occur almost without resistance.
The resistance perspective extends into further studies. For instance, Heath and Burdon (2013), in analyzing literature related to the situation in Australia, identify two types of explanation for a low level of resistance among members of the academic community. One is related to the hostile, precarious, and overloaded nature of academic work, which seems to exhaust the strength and enthusiasm required for any sort of organized resistance. The second is that neoliberal changes have happened gradually, often inconspicuously, and over a long period, depriving the academic community of their traditional academic and professional autonomy, and of their democratic rights and collegial self-governance. According to Radice (2013), this very process leads to the de-professionalization and proletarianization of the academic profession. This phenomenon, however, seems to be more complex than that. Referring primarily to the situation in the UK, Holmwood (2017, 2018) sees this process less as proletarianization and more as polarization. It creates a growing segment of proletarianized academic workers on the one hand, whose worsened working conditions promote the prerequisites for a relatively privileged and highly paid segment of senior scholars on the other hand. Such factors partly explain the lack of academics resistance to the neoliberal.
It should be again emphasized that the process of restraining, reducing, and marginalizing the university’s autonomy has steadily grown over time in a planned, systematic way. In the Swedish case, the process that Ahlbäck-Öberg and Sunberg (2016) call the ‘de-collegialization’ of the Swedish university (i.e. the conversion of collegial management to line management) began through gradual reforms in the mid 1970s. The main characteristic of this process was the government’s systematic broken promises. Each new reform was based on documents that formally and explicitly guaranteed collegial management, which, at the same time, step-by-step, was actually coming to resemble line management. In such circumstances, it is difficult to expect more organized resistance from the academic community. Additionally, it should be noted that this community has never been homogeneous; different disciplines and diverse methodological communities have been affected in different ways by these changes.
Qualitative inquiry and neoliberal research policy
The qualitative research community seems to have been, and still is, affected by the above-described changes more than others. There are at least two reasons for this. One is related to changes in research policies (or perhaps it is more appropriate to say ‘knowledge policies’) arriving at the same time as a new (neoliberal) knowledge economy. Essentially, these new policies started to involve an open academic debate around such questions as: What is good science? What are acceptable scientific methods? What are the most valuable, and therewith most desirable, scientific results? In the USA at the beginning of this century, George W Bush’s administration introduced several policy documents in which the ‘scientifically based research’ (SBR) model was prescribed as the best and most appropriate model for science (Denzin and Giardina, 2006). According to the SBR, good science must be based on an objective and reliable method via quantifiable measurement procedures that will generate data from which general scientific conclusions can be drawn. Such scientific conclusions, in turn, were deemed to represent the greatest ‘value for policy makers, practitioners, and the public’ (National Research Council, 2001, p.47, quoted in Denzin and Giardina, 2006). In essence, scientific results that do not use these methods are considered less valuable, and therefore do not merit public funding.
This research policy, as well as its definition of ‘good science,’ has been called ‘Bush science’ by its critics (Denzin and Giardina, 2006; Lather, 2006), and the methodology behind such views criticized as ‘methodological fundamentalism’ (House, 2006). In spite of this, SBR has become an important part of new research policies around the world (for a review, see Torrance (2006), but also volumes edited by Denzin and Giardina (2006, 2015, 2017). Its neo-positivistic epistemology systematically reduces science and its methods to the model derived primarily from the biomedical research tradition. A necessary consequence is that such a reduction undermines not only the autonomy of academic research, but also the individual and collective freedoms of those conducting the research. In this sort of climate, a qualitative academic community and qualitative research seem particularly exposed.
Another important reason why qualitative research is affected by neoliberal research policy lies in the different views of what research data constitute. Within the knowledge economy, data can and should be traded, thus gaining value on the market and making a profit (Koro-Ljungberg et al., 2017). Data prices, supply, demand, production, storage, distribution, and consumption are the properties imputed to the research data within the knowledge economy. Constructing research data with these properties not only results in the marginalization of researchers within the specific context of the neoliberal knowledge economy (Koro-Ljungberg et al., 2017), but also directly opposes the central epistemological and methodological principles of qualitative inquiry. To explicate, qualitative data do not have any scientific value outside the context in which they are created/constructed or without those who created the data (i.e. researchers and their informants) (Mauthner et al., 1998; Mauthner and Doucet, 2003). The meaning of data and the quality of knowledge created based on such data are completely dependent on context and relationships. As Denzin (2015, p.202) notes: ‘Data are not things that can be collected, coded and analyzed; data are processes constructed by the researcher’s interpretive practices.’
The ideal of openness
In the midst of all these negative courses affecting academia, over the past decade or so the discourse of openness has become increasingly important in a series of policy initiatives and in policy documents at both international and national levels in all OECD countries. When it comes to open access to research data, the arguments frequently mentioned in these policy documents are:
democracy and transparency – the research results financed by taxpayers’ money are supposed be available to citizens/taxpayers;
research – open access to research data and research results provides opportunities for a large number of researchers to produce more new research data and scientific results;
benefits for stakeholders outside the research community – companies, private individuals, and public authorities;
citation – open access leads to more author citations, which in turn contributes to career development.
These arguments are from Sweden (Vetenskapsrådet, 2015b), but similar arguments can be found in most other policy documents that promote open access around the world (see Mauthner and Parry, 2009).
The reason for such a triumphant march of the openness movement lies in the fact that the language of openness is powerful and persuasive (Holmwood, 2013a). As explicated, this language triggers positive transparency-related associations when used in the context of politics, fair resource distribution when used in the domain of public service, and free access to information and knowledge when used in the field of science and higher education (Holmwood, 2013a). After all, the ideals of freedom, knowledge, and justice have formed our vision of society since the Enlightenment.
‘Sapere aude!’ Immanuel Kant (1784/2014, p.9) exclaimed almost two-and-a-half centuries ago, and continued: ‘For this enlightenment … nothing more is required than freedom … the freedom to make a public use of one’s reason in all matters … [T]he public use of reason must at all times be free, and it alone can bring about enlightenment among men…’ (Kant, 1784/2014, p.59). Freedom, openness, and reason have ever since belonged to the most influential ideas, framing and governing both the development of academia and mainstream political discourses.
Within academia, one of the most prominent attempts to materialize these principles is CUDOS (communism, universalism, disinterestedness, and organized skepticism); these are ethical and methodological norms that, according to Robert Merton (1942/1973), should be the essence of good research practice. The principle of communism ensures free and equal access to all scientific assets (i.e. the collective ownership of knowledge that then promotes collective collaboration). Universalism is a scientific ethos that ensures scientific openness to all who want to contribute to its development, regardless of race, nationality, culture and gender. According to the principle of disinterestedness, scientists should always give priority to the interests of science over their individual interests and benefit. Finally, the principle of organized skepticism requires that all scientific claims should be exposed to critical scrutiny before being accepted.
At the same time, as a political ideal, one of the contemporary attempts to materialize the principle of openness is the vision of a knowledge society presented in the UNESCO world report, Towards Knowledge Societies: ‘A knowledge society should be able to integrate all its members and to promote new forms of solidarity involving both present and future generations. Nobody should be excluded from knowledge societies as it is a public good, available to each and every individual’ (UNESCO, 2005, p. 18). In such circumstances, it is extremely difficult to counteract the current discourse of openness or question the way in which current political initiatives and policy programs use the idea of openness. It is therefore necessary to observe this policy discourse within the broader context of the current economic and political changes that so-called ‘advanced’ economies are experiencing today. As noted, the main arguments on which the discourse of openness is founded are democracy, transparency, accountability, the fair distribution of public resources, and free access to knowledge.
The real goals of open-access ideology
The question that arises here is how these arguments can be defended in the light of the this discussion about economic and political trends in society in general, and in academia in particular. Essentially, the extent to which the openness argument is conceivable in the neoliberal economic context, which ‘focus[es] on competition rather than exchange … [and the] economics of competition is not about equal access or fairness, but rather privatization, enterprise, and capital’ (Cannella and Lincoln, 2015, p.56), is debatable. It becomes a matter of exploring how open access should be discussed in the context of a knowledge economy where knowledge increasingly becomes a commodity and, like other commodities, becomes more accessible to some groups and individuals than others.
How can we discuss open access in the context of a university’s autonomy being attacked, reduced, and marginalized? Here, external, non-academic (power) instances not only impose new – and, for academia, so far unknown – criteria, such as accountability, performance, quality assurance, and good practice, but also try to impose ideas about what good research is, which scientific method to prioritize, and what good data are. The university in which the de-professionalization, polarization, and proletarianization of the academic profession is occurring, and where the additional phenomenon of the panoptic supervision and control of university employees is evident, does not have much in common with the idea of open access.
The idea of open access, understood from the Kant-Merton-UNESCO knowledge society tradition, has little in common with the actual processes of the enormous strengthening of private property laws on the one hand, and with university technology transfer offices, science and technology research parks, incubators, and so on (Mirowski, 2012; Jessop, 2017) on the other. At the same time, national research councils demand no return on patents resulting from the research they fund (for the US, see Argyres and Liebeskind, 1998; for the UK, see Holmwood, 2013a), which turn intellectual commons, created with the help of public funding and intended to be used to benefit all citizens, into intellectual properties. However, this is not the only way of converting public resources into private properties. With the support of open-access initiatives, now even research data collected within ‘publicly funded’ research projects are becoming open to an increasing number of private research companies that are often working with Big Data, including these publicly funded data, in their data sets, and analyzing and producing research results under patent (Holmwood, 2013a). Overall, it now seems clear that the discourse of openness, with the help of rhetoric based on the academic values that develop from Kant, through Merton to UNESCO’s knowledge society document, tries to achieve goals entirely opposed to that rhetoric. The real goal is the promotion of the neoliberal knowledge economy in which not only scholars will be hired and exploited by neoliberal capitalism, but so will knowledge itself. In what follows, I shall try to determine the extent to which this has applied to the Swedish national research policy over the past two decades or so.
Swedish national research infrastructure
The development of the Swedish national research infrastructure has been described as one of the most important projects the Swedish Research Council has been involved with since the beginning of the new millennium. The ambition has been to provide the preconditions for researchers to carry out research of the ‘highest scientific quality’ within all subject areas. Increased openness in researchers’ use of infrastructural resources and data has been one of its primary strategic aims. The first concrete steps were taken in 2005, when the Swedish Research Council established the Research infrastructure committee (KFI) with the task of creating a strategy for building the Swedish research infrastructure. The committee’s work resulted in the Swedish Research Council’s Guide to Infrastructure (Vetenskapsrådet, 2006), describing the necessary long-term conditions for the future development of Swedish research. Since then, there have been three more editions of the guide (Vetenskapsrådet, 2007, 2011, 2015a), complete with amendments (Vetenskapsrådet, 2016). A brief analysis of the content of these documents offers a relatively clear picture of the development of Swedish research policy over this period.
The first thing to remember is that behind all these issues is the Swedish Research Council, an authority under the Ministry of Education, which is formally governed by the legislative document Instruction for the Swedish Research Council (Svensk Författningssamling, 2009, § 1), issued by the Swedish government. According to this document, the main task of the council is to provide support for basic research of the highest scientific quality in all scientific fields. Thus, the focus on basic research, defined as a systematic and methodical search for new knowledge and ideas without a specific application in mind, is central to this document. In contrast, applied research searches for new knowledge with a specific application in mind.
Within the knowledge economy, the third function of knowledge is introduced, namely development, under the common name of research and development (R&D). According to the OECD Frascati Manual (OECD, 2015, p.29), one of the most influential international documents promoting R&D, the relationship between basic/applied research and development is defined not only as complementary, but also as hierarchical. Thus, basic research is, according to the manual, ‘work undertaken primarily to acquire new knowledge … without any particular aim or use in view’ (OECD, 2015, p.29). Applied research is supposed to have greater value, or at least be more meaningful, because it involves acquiring new knowledge that is ‘directed primarily towards a specific, practical aim or objective’ (OECD, 2015, p.29). Finally, the highest value is given to development, which is based in and includes both basic and applied research, but also produces ‘additional knowledge, which is directed to producing new products or processes or to improving existing products or processes’ (OECD, 2015, p.29). One additional feature of R&D in general, and the Frascati manual in particular, is the promotion of a new type of science classification that differs from the traditional classification of academic disciplines and is more suited to industries that might benefit from the results in these areas. For example, there are categories such as engineering and technology, agricultural and veterinary science, material sciences, life sciences, and energy research.
If we return to the discourse on the development of the Swedish research infrastructure featured in the four editions of the guide, the 2006 edition still provides a traditional classification of academic disciplines, with a marginal inclusion of a category for material sciences. In the 2014 edition, however, the focus is on seven subject-specific categories: material science; physics and engineering sciences; energy research; environmental sciences; humanities, culture, and society; life sciences; and e-sciences. This is the first indication of the Swedish infrastructure promoting the R&D/knowledge economy rather than basic research. To illustrate:
Attractive research centres are not only positive for the advancement of research, they also generate ideas for innovations, influence the social climate, offer incentives to attract talent, etc. This, in turn, provides an argument for corporations needing advanced expertise and development to establish themselves near these centres. (Vetenskapsrådet, 2008, p.11)
Phrases such as ‘generate ideas for innovations,’ ‘attract talent’ and ‘argument for corporations’ may all be understood to an extent as the (un)intended consequences of a successful policy that focuses primarily on basic research. However, all four editions of the guide are full of similar formulations, such as ‘investments in infrastructure,’ ‘investments in research,’ ‘provide scope of outstanding research,’ ‘world-class research,’ ‘be of broad national interest,’ and ‘be easily accessible to researchers, industry and other stakeholders.’ Even if we try to avoid drawing categorical conclusions (for example, that the documents generally focus on competition rather than exchange, or that there is an obvious trend toward the marketization and privatization of basic research), one solid conclusion is that this sort of vocabulary and such formulations, which normally belong to the neoliberal knowledge economy discourse, are completely absent from the Instruction for the Swedish Research Council (Svensk Författningssamling, 2009), the main legislative document governing the work of the council.
An additional significant feature of the discourse that dominates the guides is the researchers’ role in infrastructure functioning. Proclaimed expectations of research infrastructures are not only to make long-term plans for scientific goals and funding, but also for research utilization. They are also responsible for making plans for accessibility (to the infrastructure, research data, and research results) for other researchers, industry, and stakeholders (Vetenskapsrådet, 2015a, p.16). However, these functions are largely delegated to researchers themselves, who are already expected to develop plans for the utilization and accessibility of their expected research results within funding applications.
Although data management plans will be discussed later, what is important to note here is the uncertainty among researchers in terms of participating in these processes. This is often interpreted as the lack of a necessary data management culture, which then needs to be established and developed, and is offered to the researchers in the form of comprehensive assistance and support from librarians, archivists, lawyers, and IT engineers. Here, as we have seen, researchers are not only being deprived of their academic autonomy, but are also being transformed from subjects of their research work into the objects of research policy. This policy is created somewhere else, and results in librarians, archivists, lawyers IT engineers and their ilk occupying a more important position than the researchers themselves.
Scientists are, therefore, gradually becoming knowledge workers (within the knowledge economy) rather than scientists. Likewise, they are increasingly becoming the objects of different instructions and training (‘user support’). The epistemological principles defining what science and knowledge are, what kind of knowledge is valuable for outlining the goals of science, and what methodological principles and scientific methods define how to achieve these goals are increasingly being formulated outside academia, or with the participation of only selected representatives of the scientific community.
Such trends have been recorded, analyzed, and criticized by several studies over the last decade (see for example Bennich-Björkman, 2007, 2013; Karran, 2007; Karran et al., 2017). A recent comparative study of academic freedom in 28 EU countries is based on five relevant dimensions: academic freedom for teaching and research, institutional autonomy, self-governance, academic tenure, and adherence to international agreements (Karran et al., 2017). The results show that Sweden occupies position 23 out of the 28 countries covered by the study. Sweden achieves particularly low scores when it comes to self-governance in legislation, academic freedom in legislation, and institutional freedom in legislation (Karran et al., 2017, p.229).
Creating conditions for the archiving and reuse of research data
One of seven priority sub-projects within the infrastructure project was in the field of humanities and social sciences. An expert group for Database Infrastructure (DISC) was set up in 2006 with the task of establishing databases and developing effective tools for sharing research data. For the more practical work in this context, the Swedish National Data Service (SND) was founded in 2007, with the main duty to secure technical, administrative, legal and educational resources for the collection, storage, and reuse of research data (both quantitative and qualitative). Nevertheless, this project has never realized its full potential, mainly because of the existence of a major legal obstacle, namely the Personal Data Act (Svensk Författningssamling, 1998). The Act states that it is illegal to use research data for anything other than the specific project for which the data were collected. This has resulted in a paradoxical situation: the SND prepares the infrastructure for archiving and reusing data, and even encourages researchers to deposit their data in the archive, while simultaneously being unable to allow researchers to reuse archived data because this is illegal.
At the same time, some voices from the academic community have criticized the infrastructure project for having simplistic and rigid views of such concepts as scientific data, investigation methods, and the differences between qualitative and quantitative data (Slavnic, 2011). The project was also criticized for being primarily founded on neo-positivist, foundationalist epistemology, according to which qualitative data is and should be treated in the same way as quantitative data. Furthermore, the entire process of developing an infrastructure for data archiving and sharing took place without the active participation and/or adequate representation of researchers involved in qualitative research (Slavnic, 2011, 2013). Another seven years passed before the next major steps in the data archiving and sharing project were taken. In what follows, two significant policy initiatives and the resulting documents that were released are discussed.
The first initiative began on 17 January 2013, when the government appointed a commission charged with investigating the conditions for register-based research in Sweden (Dir, 2013, p.8). The main task of the investigation was dealing with the legal obstacles to archiving and sharing research data. This work resulted in the official report on register-based research in 2014 (SOU, 2014). The investigation’s main ambition was to provide better conditions for archiving and reusing research data, while at the same time protecting the personal integrity of the people being studied. The solution was found in a combination of §13 in the Personal Protection Act (PUL)1 and §3 in the Act concerning the Ethical Review Act (Ethical Review of Research Involving Humans).2 Even if the PUL prohibits using research data for any purpose other than those for which the data have been collected, §13 offers an exception to this rule; that is, a researcher may get support for processing sensitive personal data if formally approved by an ethics review board. This exception is also supported by §3 in the Ethical Review Act.
The investigation concluded that research databases do not represent significant violations of personal integrity, but it was nevertheless necessary to provide clear legal support for these activities. In this regard, legislative amendments to several existing laws,3 as well as an entirely new law (The Law on Research Databases), were proposed. This new law, which should have come into force on 1 January 2016, was supposed to propose only general rules, while each database would be complemented with its own specific regulations governing purpose and content. In addition, each research project applying for data (re-)use would always need formal approval from an ethics review board.
The report was sent out for public consultation in November 2014, with the consultation period lasting until the spring of 2015. Several powerful institutions, such as the Swedish Research Council, FORTE (Swedish Research Council for Health, Working Life, and Welfare), the Karolinska Institutet, and some big pharmaceutical companies, were positive about the proposal, while others, such as the Data Inspection Board and the Swedish Disability Federation (an umbrella organization with 37 institution members), were less enthusiastic (Engelmark, 2015).
Harmonizing national regulations with EU regulations
Further work on the introduction of the proposed law ceased abruptly at the beginning of 2016 when it became clear that the new EU General Data Protection Regulation (GDPR) 2016/679 (EU, 2016) would come into force on 25 May 2018 and replace all national personal data regulations. The Swedish government had already appointed a commission in February 2016 (Dir, 2016, p.15) to determine how national regulations had to be adjusted in relation to the new GDPR. An official report (SOU, 2017 was presented in May 2017). This policy document proposed several national regulations that would supplement the GDPR, but only at the general level, without entering into specific regulatory spheres, such as archiving and reusing research data.
The second initiative, drafting the national guidelines for open access to scientific information, started at around the same time as the first. The task was given to the Swedish Research Council on 13 December 2012. As stated earlier, it was illegal for the data collected within the framework of a specific research project to be used for other purposes, within other projects, or by other investigators. Thus, the government started these two initiatives simultaneously. The first was to examine new legal frameworks within which it would be possible to have open access to data; the second, which is dealt with in the following passages, was to create guidelines for open access to scientific information.
The proposal of the guidelines was based on the EU Commission’s recommendations on access to, and the preservation of, scientific information – C4890 (EU, 2012). According to this, member states were required to draw up national guidelines for open access and formulate an inclusive plan for its implementation, monitoring, and funding. The main arguments for the promotion of open access to research data this document relied on were that it was good for democracy, transparency (‘Research results paid for by public funds should, as the matter of principle, be accessible for citizens’) (research (to address new questions in the same field, to address new problems in other fields, and to avoid repeating experiments), innovation, utilization outside research, and finally, researchers (because it leads to an increased number of citations) (Vetenskapsrådet, 2015b, p.16). The proposal even contained certain limitations with reference to the main principle of open access to research data. These limitations were related primarily to personal data that were regulated by laws and the protection of personal integrity, to data that might threaten the nation’s security, and research data that have commercialization value (Vetenskapsrådet, 2015b, p.17).
According to the proposal, the strategic goal was that research data, wholly or partly produced with the help of public funding, should be openly accessible by 2025. This objective would be accomplished in three stages (Vetenskapsrådet, 2015b, pp.18–24). Between 2015 and 2020, several pilot calls would be announced with the requirement of open access to collected empirical data. Between 2020 and 2025, the major evaluation of the first implementation stage would be conducted, and the proposal to government on how to proceed with the project would be submitted. Finally, in 2025, open access to all scientific information would be in place.
The document was sent to the government in 2015 (Vetenskapsrådet, 2015b). More than two years have passed since then (this text written in the summer of 2017), and almost half of the first, crucial, implementation phase of the project has already gone without any pilot calls announced. This is because the proposal has never been adopted by the government and the legal framework that would make it possible is still not in place. As such, the whole process has been suspended in expectation of the new EU regulation coming into force in May 2018.
Data management plans at the university level
Even though the process has been suspended, it has not prevented infrastructure preparation for open access. Over the past couple of years, almost all Swedish universities have produced some kind of status report and proposals for further work related to open access for research data. Apart from the guideline proposal (which is still not formally adopted), support for this work on data management plans has also been found in political documents issued in the meantime,4 and in the SND’s guidelines for data management. These contain detailed instructions about data documentation and the creation of data management plans.
A glimpse at these status reports reveals the primary involvement of university administrators, librarians, and IT staff. Thus, in Lund University’s report, the conclusions were based on interviews with only faculty management representatives and library staff from eight faculties (Johnsson and Lassi, 2015). Further, Stockholm University’s report was produced by a project group consisting of representatives of the university’s administration (archive, library, research support, IT, planning, and management support) and research representatives from the humanities and natural sciences (Stockholms Universitet, 2016, p.3). However, looking at the list of participants involved in this example indicates that only two of the 11 were research representatives; one of whom was a dean, which means it is unclear whether he was representing the research community or research leadership. Nevertheless, Malmö University’s report (Fransson et al., 2016) differed in certain ways from this pattern as questionnaires were sent to all professors, doctoral students, and lecturers. What is indicative, however, is that only 161 individuals, or 27%, completed them.
Conclusion
The first part of this paper introduced some important courses, forces, and discourses of open access policy initiatives in OECD countries. The main characteristic of this development is a discrepancy between the rhetoric of democracy, transparency, and accountability on the one hand, and the real goals of promoting the neoliberal knowledge economy, or values of academic capitalism to use Slaughter and Rhoades’ (2004) formulation, on the other. The second part of the paper attempted to determine the extent to which the development of national research policy in Sweden is in line with these international trends. Without the ambition of drawing conclusions that are too categorical – which, of course, requires additional research – the results can be summarized in the following points.
First, there is a noteworthy discursive discrepancy between the tone and formulations in the main policy document on the task of the Swedish Research Council (Svensk Författningssamling, 2009), and the tone, rhetoric, and formulations in documents and policy initiatives concerned with research infrastructure development. One example of such a discursive declination from the main policy document is the way in which infrastructure policy documents classify the sciences, which is closer to the OECD Frascati Manual (2015) (promoting R&D) than to the Instruction for the Swedish Research Council (Svensk Författningssamling, 2009) (promoting and supporting basic research). Furthermore, science and its ontological and methodological foundations are treated implicitly as a monolith, without any varieties and variations in terms of different academic cultures and traditions, and without any differences between social and natural sciences or between quantitative and qualitative methods. When it comes to archiving and open access to research data, a neo-positivist epistemology is dominant, treating qualitative data in the same way as quantitative data.
This paper has also shown that research strategies, tasks, and even methods are increasingly being formulated outside academia. They are, of course, not imposed directly, but rather often subtly and indirectly via the criteria for long-term research funding. Those who do not live up to these criteria cannot secure funding for their research and therefore cannot conduct this research. These trends in research policy, however, have not yet assumed such proportions that they can be characterized as Bush science, but tendencies of restraining and reducing the autonomy of the university as an institution and the autonomy of individual scholars are obvious. When it comes to archiving and reusing qualitative data, lack of interest among researchers is often interpreted as lack of an archiving culture that needs to be initiated and encouraged by the new infrastructure policy. Researchers are to be indoctrinated in a new (archiving) culture composed of rules, routines, and values taught to them by librarians, archivists, and IT professionals.
Yet another problematic phenomenon characterizes the work of preparing the infrastructure for archiving and reusing data from the outset. The archiving project has so far been impossible to implement for the simple reason that it is illegal. The obstacle was the Personal Protection Act (PUL), which prohibits the use of empirical data for any purpose beyond the project within which these data are collected. The Research Council (VR) and others institutions involved in the project may realize that PUL is a problem. However, the only legitimate way to progress is to initiate a political process to change the law (in this case, PUL). When the new law is adopted and comes into force, meaning that archiving and reusing qualitative data will become legal, an infrastructure will need to be created for these purposes. Instead, over the past decade, a large and expensive infrastructure has been developed for a project that has inevitably been illegal. This is ethically, legally, and politically unsound.
The new EU regulation that came into force on 25 May 2018 has been described by relevant institutions (including the SND and its lawyers) as a legal document that will, in a quite satisfactory manner, enable both the full protection of personal data and the opening up of data archiving and reuse. Whether this is possible and how, however, remains to be seen. In any case, the new reality will force researchers to take a clear stance on these issues, something that has been conspicuous in its absence.