1. bookVolume 5 (2020): Issue 4 (November 2020)
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Journal
eISSN
2543-683X
First Published
30 Mar 2017
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English
access type Open Access

The Association between Researchers’ Conceptions of Research and Their Strategic Research Agendas

Published Online: 21 Nov 2020
Volume & Issue: Volume 5 (2020) - Issue 4 (November 2020)
Page range: 56 - 74
Received: 09 Jan 2020
Accepted: 20 Jul 2020
Journal Details
License
Format
Journal
eISSN
2543-683X
First Published
30 Mar 2017
Publication timeframe
4 times per year
Languages
English
AbstractPurpose

In studies of the research process, the association between how researchers conceptualize research and their strategic research agendas has been largely overlooked. This study aims to address this gap.

Design/methodology/approach

This study analyzes this relationship using a dataset of more than 8,500 researchers across all scientific fields and the globe. It studies the associations between the dimensions of two inventories: the Conceptions of Research Inventory (CoRI) and the Multi-Dimensional Research Agenda Inventory—Revised (MDRAI-R).

Findings

The findings show a relatively strong association between researchers’ conceptions of research and their research agendas. While all conceptions of research are positively related to scientific ambition, the findings are mixed regarding how the dimensions of the two inventories relate to one another, which is significant for those seeking to understand the knowledge production process better.

Research limitations

The study relies on self-reported data, which always carries a risk of response bias.

Practical implications

The findings provide a greater understanding of the inner workings of knowledge processes and indicate that the two inventories, whether used individually or in combination, may provide complementary analytical perspectives to research performance indicators. They may thus offer important insights for managers of research environments regarding how to assess the research culture, beliefs, and conceptualizations of individual researchers and research teams when designing strategies to promote specific institutional research focuses and strategies.

Originality/value

To the best of the authors’ knowledge, this is the first study to associate research agendas and conceptions of research. It is based on a large sample of researchers working worldwide and in all fields of knowledge, which ensures that the findings have a reasonable degree of generalizability to the global population of researchers.

Keywords

Introduction

An understanding of the research process is central to fostering the development of innovative knowledge that can be used to tackle the complex global challenges faced by humanity (Hoolohan, Mclachlan, & Larkin, 2019). In the ongoing race for knowledge advancement and innovation, governments and organizations face pressure to make informed decisions about how best to allocate research funds, improve current policies and incentive frameworks, and promote quality research (Vaesen & Katzav, 2017). Increasing resources are now being invested in research endeavors, leading to more knowledge being produced, even though a managerialism drive has impaired knowledge breakthroughs (Horta & Santos, 2019a). Most of our understanding of knowledge production relies on studies of research productivity and performance, both descriptive and inferential; such studies are informative and useful but are focused mostly on finalized research products such as papers and related bibliometric information complemented by demographic and institutional characteristics (Young, 2015) and additional perspectives are needed.

An understanding of how researchers’ mindsets and beliefs are associated with their strategic research approaches is just as pivotal to comprehending the knowledge creation process as an understanding of how environmental frameworks and other determinants shape research production. However, although there is a substantial body of research on the latter (e.g. Bentley, 2014), minimal attention has been paid to the former. Researchers and scientists have not achieved consensus on researchers’ own conceptions of research (Fuller, 2012). Conceptions of research matter because the cultural and social ethos guiding the researcher's thinking and beliefs about research—and science in general—influence the motivations, decisions, and aptitudes related to engagement in research choices and interests (Niiniluoto, 2020). This study addresses this research gap and advances recent studies on researchers’ preferences for specific research agendas, the majority of which have focused only on a single field or discipline (Foster, Rzhetsky, & Evans, 2015; Horta & Santos, 2016; Ying, Venkatramanan, & Chiu, 2015). This exploratory study aims to answer the following research question: what are the associations between researchers’ conceptions of research and their preferences for strategic research approaches? The study is based on two inventories: the Conceptions of Research Inventory (CoRI) (Meyer, Shanahan, & Laugksch, 2007) and the Multi-Dimensional Research Agenda Inventory—Revised (MDRAI-R) (Horta & Santos, 2020).

Methodology
Inventories used to measure research beliefs and agendas

The CoRI (Appendix 1), developed by Meyer, Shanahan, and Laugksch (2007), comprises five distinct dimensions that collectively represent the views that an individual holds about research. The original CoRI inventory focused on a population of postgraduate students (mostly doctoral students) and academic staff from nine countries, but an overwhelming majority of respondents were from Australia, South Africa, and Finland. CoRI is a follow-up to a previous inventory focused on Australian and South African postgraduate students’ conceptions of research, SCoRI, which the authors published two years earlier (Meyer, Shanahan, & Laugksch, 2005). To the best of our knowledge, the current study is the first to apply the CoRI solely to a population of researchers, with no postgraduate students. The dimensions of CoRI are as follows. Research as the discovery of truth places truth-seeking goals at the center of research, an idea associated with the research “layer” conception, which is defined as “a process of discovering, uncovering or creating underlying meanings” (Pearson & Brew, 2002). Research as an insightful process treats research as a process through which new insights are generated on a topic. Research viewed as re-search perceives research as a search for something that has been overlooked. Finding solutions to problems views research largely as a problem-solving activity that involves answering specific questions and searching for solutions. Misconceptions about research evaluates a respondent's misconceptions regarding research activities, such as the belief that results are guaranteed if the methods are sound or that publication of a given study automatically means that it is reliable.

The MDRAI-R (Appendix 2) comprises eight distinct dimensions that influence the way researchers approach their strategic research agenda (Horta & Santos, 2020). The MDRAI-R was developed after the MDRAI, which focused primarily on academics conducting research in the field of social sciences (Horta & Santos, 2016). The MDRAI-R has dimensions that are mostly consistent with those of the MDRAI, and it has been validated for researchers from all fields of knowledge, developing research inside and outside academia, and working in 154 countries. The dimensions of the MDRAI-R are as follows. Scientific ambition stresses research that is likely to provide recognition for one's work and to contribute to achieving a position of intellectual and scientific authority in a field (Latour & Woolgar, 2013); it also relates to determination to publish research work. Collaboration combines the desire to collaborate with others and openness to invitations by others to collaborate on research projects (Bozeman & Gaughan, 2011). Divergence refers to an interest in various topics and a preference for working on multidisciplinary and/or interdisciplinary research (Abramo, D’Angelo, & Costa, 2018). Discovery is the preference to focus on topics that have the potential to achieve breakthroughs and thus measures the willingness to engage in riskier projects (Popper, 2005). Tolerance of low funding represents a willingness to focus on research topics even when the available funding is scarce (Ebadi & Schiffauerova, 2015), and thus it also includes an element of risk that may be influenced by organizational pressures. Mentor influence refers to the degree to which the PhD mentor influences a researcher's research plans (Hemmings, 2012). The degree to which the research agenda is academia-driven indicates how much a researcher is influenced by scientific priorities for which consensus has been reached by the scientific community (an attribute that is more common among physicists than, for example, sociologists; Becher & Trowler, 2001). This dimension also evaluates the degree to which the research agenda is aligned with the strategic targets and pressures imposed by the institution where the researcher is currently working. The extent to which the research agenda is society driven depends on the incidence of social challenges as focal points of research interest and the degree of consultation with and participation of laypersons and non-experts in setting the agenda (Kaiser & Leiner, 2011). Higher scores indicate greater alignment with the defining characteristics of the dimensions.

Data

Using a global sample of 8,555 researchers from all fields of science, a series of ordinary least squares (OLS) regressions (Hair et al., 2007) were conducted to determine the effects of conceptions of research on research agenda setting. Analysis of the OLS residuals was conducted to evaluate the OLS assumptions—notably, homogeneity of variance, linearity, and normality (Hair et al., 2007). The results of this exercise indicated a random pattern of residuals uniformly distributed around the origin coordinates of the scatterplot, which is expected when OLS assumptions are met (Hair et al., 2007). The sample was obtained by identifying authors of published papers in scientific journals indexed in the Scopus database that were published between 2010 and 2016. These authors were invited via e-mail to participate in a survey that took place between June 2017 and August 2018. The instrument included questions about demographics, education, and professional career path, and items from the two instruments described above (CoRI and MDRAI-R). The questions for these instruments were presented to participants in random order to mitigate any bias arising from the question order. In total, 21,106 individuals agreed to participate. However, 12,551 dropped out of the survey without completing the blocks required for this analysis (MDRAI-R and CORI), and they were therefore excluded from the analysis. The sample had global coverage, with a large number of participants in major scientific powerhouse nations, including the US, the UK, France, and Italy. The sample had a greater proportion of male (N = 5,691) than female (N = 2,864) researchers, and an average age of around 51 (M = 50.751, SD = 12.034), which aligns with the global population of researchers. In accordance with the literature (Horta & Santos, 2020; 2019b), several control variables were used: gender, age, time elapsed since obtaining the Ph.D., Field of Science (FoS), whether the institution is top-ranking (in the top 500 of the Leiden Ranking, sorted by publication count using fractional counting), and career internationalization, which indicates whether the researcher is working in a country other than their country of birth (Horta, Jung, & Santos, 2019). Country was also controlled for in the analysis, but it is omitted from the results table for readability. The descriptive statistics of the dependent, explanatory, and control variables are summarized in Table 1.

Descriptive statistics.

Quantitative VariablesMSD
MDRAI-R dimensions (Dependent variables)Scientific Ambition5.0730.946
Divergence5.0670.918
Collaboration5.1890.826
Mentor Influence2.9061.407
TTLF4.2101.339
Discovery5.5050.922
Academia Driven4.0311.040
Society Driven4.0661.121
CoRI dimensionsTruth-seeking, research as3.8720.982
Misconceptions about research2.6580.949
Problem-solving, research as3.8040.728
Re-research, research as3.5430.743
Insightful process, research as4.3020.530
Control VariablesAge50.75112.034
Years Since PhD18.12912.533
Qualitative VariablesN%
Gender
  Male5,69166.52%
  Female2,86433.47%
Field of Science (FoS)
  Natural & Agricultural Sciences2,49929.21%
  Engineering and Technology1,76120.58%
  Medical and Health Sciences1,98723.23%
  Social Sciences2,04923.95%
  Humanities2593.02%
Research University (top 500)
  Yes1,83821.48%
  No6,71778.51%
Career internationalization
  Yes6,42375.08%
  No2,13224.92%

The descriptive statistics of the sample concerning the MDRAI-R show that discovery, collaboration, scientific ambition, and divergence had the highest scores, suggesting that most researchers characterize their research agendas as risk-taking, with the potential to attain disruptive new findings, collaborative, multidisciplinary (which may involve a degree of interdisciplinarity), and scientifically ambitious—or at least, having the potential to increase the researcher's profile in the field. Mentor influence was the lowest score dimension, possibly because in some cases, over the course of career advancement, contact with the PhD mentor decreases or is lost, perhaps because the interests of the researcher diverge from those of the PhD supervisor and from the topic of the doctoral studies, or because the mentor has passed away, as most of the respondents had substantial seniority and research experience (average time since PhD was 18 years, and the average age was 50). The descriptive statistics for the CoRI indicate that the most frequently held view of research is research as an insightful process, followed at a relative distance by research as truth seeking and research as problem-solving. Most of the researchers in the sample had low agreement with misconceptions about research.

Results

The results of the OLS analysis are summarized in Table 2.

Effects of conceptions of research on research agenda setting.

AmbitionDivergenceCollabMentorTTLFDiscoveryAcademiaSociety
Truth0.069*** (0.011)−0.034*** (0.011)−0.008 (0.010)0.021 (0.017)−0.025 (0.016)0.048*** (0.011)−0.026** (0.012)−0.114*** (0.013)
Misconceptions0.056*** (0.013)0.014 (0.013)−0.026** (0.012)0.277*** (0.020)0.078*** (0.019)−0.040*** (0.013)0.165*** (0.014)0.150*** (0.015)
Problem-solving0.064*** (0.016)0.157*** (0.016)0.127*** (0.015)0.034 (0.025)−0.044* (0.024)0.068*** (0.016)0.113*** (0.018)0.310*** (0.019)
Re-research0.104*** (0.016)0.025 (0.016)0.029** (0.014)0.087*** (0.024)0.017 (0.023)−0.020 (0.016)0.085*** (0.017)0.030* (0.018)
Insightful process0.258*** (0.021)0.118*** (0.021)0.241*** (0.019)−0.127*** (0.032)0.085*** (0.030)0.312*** (0.021)−0.030 (0.023)−0.060** (0.024)
Gender (Male)0.091*** (0.022)−0.010 (0.022)0.030 (0.019)0.034 (0.033)0.237*** (0.032)0.101*** (0.022)−0.172*** (0.024)−0.121*** (0.025)
Age−0.020*** (0.002)−0.007*** (0.002)−0.002* (0.001)−0.006** (0.002)0.022*** (0.002)0.001 (0.002)0.000 (0.002)0.016*** (0.002)
Time since PhD0.010*** (0.002)−0.002 (0.002)0.004*** (0.001)−0.024*** (0.002)−0.005** (0.002)0.005*** (0.002)−0.016*** (0.002)−0.021*** (0.002)
Research universities (top 500)0.046* (0.026)0.020 (0.026)0.009 (0.023)0.031 (0.039)−0.053 (0.037)0.054** (0.026)−0.134*** (0.028)−0.080*** (0.030)
FOS (Engineering and Technology)−0.034 (0.028)0.157*** (0.029)−0.078*** (0.025)0.021 (0.043)0.046 (0.041)0.129*** (0.029)0.072** (0.031)0.444*** (0.032)
FOS (Medical and Health sciences)0.075*** (0.028)0.082*** (0.028)0.140*** (0.025)0.142*** (0.043)−0.120*** (0.041)0.015 (0.028)0.154*** (0.031)0.389*** (0.032)
FOS (Social sciences)0.089*** (0.028)−0.061** (0.028)−0.010 (0.025)−0.002 (0.043)0.488*** (0.041)0.067** (0.028)−0.172*** (0.031)0.628*** (0.032)
FOS (Humanities)0.119** (0.059)0.044 (0.060)−0.229*** (0.053)−0.231** (0.090)0.743*** (0.086)0.245*** (0.060)−0.355*** (0.064)0.398*** (0.068)
Career internationalization0.098*** (0.024)0.087*** (0.024)0.017 (0.022)−0.136*** (0.037)0.107*** (0.035)0.137*** (0.024)0.003 (0.026)−0.074*** (0.028)
Country controlsYesYesYesYesYesYesYesYes
Observations8,5548,5558,5547,9208,5518,5548,5548,551
R-squared0.1470.0790.1080.1720.1030.0890.1630.206

Notes: Standard errors in parentheses.

p < 0.01,

p < 0.05,

p < 0.1

Because of the large sample size, most of the effects were significant, and we therefore focused on the findings with the largest coefficients due to their expected practical significance.

The conception of research as the discovery of truth showed several significant effects, but the most notable was a negative association with a society-driven orientation (B = −0.114, p < 0.01). A possible interpretation is that research focused on societal issues is likely to be more applied in nature and thus not directly related to the idea of research as a “truth-seeking” process, which may be considered more theoretical and abstract. However, this seems to stand in opposition to the focus on truth-seeking from a citizen science perspective, where non-professionals participate in scientific research with a “truth-seeking” purpose and focus on a mix of applied societal and scientific challenges (Wynn, 2017). The dimension misconceptions about research also showed several interesting effects, with high scores on this dimension associated with a high level of mentor influence (B = 0.277, p < 0.01), increased tolerance of low funding (B = 0.078, p < 0.01), and a higher orientation toward an academia-driven (B = 0.165, p < 0.01) and society-driven (B = 0.150, p < 0.01) approach. The link with mentor influence suggests that a researcher following a specific approach may feel more confident with the presence of a mentor, who provides a sort of guarantee that the chosen approach is valid. A researcher's misconception about research may derive from socialization with the mentor during the doctoral studies. The same rationale holds for the association of misconceptions about research and the academia-driven dimension of the MDRAI-R. A researcher may feel confident about a specific research approach or conceptualization if he or she perceives that this research process is supported, accepted, or promoted institutionally, such as by a scientific community, university, or industrial research laboratory, as these organizations’ backing confer legitimacy on one's actions and may be perceived by the researcher as holding the ultimate responsibility (Milgram, 1974). The association with low available funding may reflect the researcher's difficulties in obtaining research funds if the research approach is considered flawed by research funding agencies. Finally, engaging with peers outside academia through collaboration with laypersons may increase a researcher's confidence that their research process will achieve successful results because the researcher assumes the role of an expert who is in control of the research process (this may be the case even if the conceptualization or methods are flawed but the researcher believes they are sound; Gorman & Gorman, 2017).

The conception of research as problem-solving had positive associations with divergence (B = 0.157, p < 0.01), collaboration (B = 0.127, p < 0.01), and academia-driven (B = 0.113, p < 0.01) and society-driven (B = 0.310, p < 0.01) approaches. These results are consistent with the expectation that problem-solving implies a need to engage in multidisciplinary and collaborative research processes that are aligned with the field and, more specifically, with institutional policies and incentives, and are focused on “real-life” problems that involve the participation of non-experts in the research process (Lyall, 2019). Conceiving of research as re-research shows a number of weaker effects, the most notable of which were on scientific ambition (B = 0.104, p < 0.01), mentor influence (B = 0.087, p < 0.01), and academia-driven (B = 0.085, p < 0.01), and society-driven (B = 0.030, p < 0.1) approaches. The association with scientific ambition can be explained by the need to assess the findings of others and drive them forward, thus reinforcing one's field position within what Kuhn (2012) calls “normal science,” or attempting to create a disruptive paradigm. Both are known to be pathways to authority within a field and to career success in research. The influence of the mentor and orientation toward academia-driven dimensions may be associated with research agendas that revisit research work, and the orientation toward society-driven work might indicate a need to reassess and update past findings as societal challenges and knowledge evolve at different paces. Viewing research as an insightful process showed notable positive associations with scientific ambition (B = 0.258, p < 0.01), collaboration (B = 0.241, p < 0.01), and discovery (B = 0.312, p < 0.01), with an additional negative association with mentor influence (B = −0.127, p < 0.01). These results stress the continuous struggle to find new perspectives that can lead to knowledge breakthroughs in specific topics and indicate that this struggle demands determination (associated with scientific ambition), collaboration to deal with the complexities of science, and risk-taking attitudes rather than conformity (Santos & Horta, 2019a). Finally, it is relevant to note that all of the dimensions of the CoRI showed statistically significant and positive associations with one MDRAI-R dimension: scientific ambition. This means that no matter which conceptualizations of research one believes in—and some researchers’ beliefs may include an overlap of several, even if one is dominant (Brew, 2001)—striving for scientific recognition and authority in one's field continues to be a key objective of most researchers. This finding underlines the strongly rooted Foucauldian and Mertonian dynamics in contemporary science systems (Stehr & Grundmann, 2011).

Some interesting findings were made in relation to the control variables. When strategizing on research agendas, scientific ambition, discovery, and tolerance for low funding played a greater role for male researchers, while female researchers paid more attention to environmental factors such as academia-driven and society-driven approaches. These findings align with expectations based on the literature that male and female researchers face different institutional and organizational constraints on their work, which affect their thinking and beliefs about research practices, aims, and productivity, ultimately undermining female researchers from attaining intellectual leadership roles in epistemic communities (Oleksiyenko & Ruan, 2019). Female and male researchers also differ in terms of research preferences and work strategies, as female researchers tend to be more focused on issues of social innovation and knowledge exchange and are more likely to abide by institutional norms and values, whereas male researchers assume a more individualistic approach and are more career-focused and interested in establishing themselves in scientific communities as leading scientists (Ramos et al., 2015). Time since completing the PhD was more relevant than age to the development of research agendas, highlighting the growing importance of professional age in research endeavors compared with life age (Gaughan, 2009). This is further reinforced by the fact that the findings concerning these two variables differed substantially, perhaps because researchers’ careers are increasingly nonlinear and diverse in terms of time of entry into the career (Jaeger et al., 2017). For example, older researchers may be less ambitious in their research agendas (B = −0.020, p < 0.01), but the more professional experience a researcher has, the more ambitious their research agenda will be (B = 0.010, p < 0.01). Those working in the most prestigious universities were more focused on potentially disruptive research processes and more willing to drive forward ambitious research agendas (B = 0.046, p < 0.01), and they placed considerably less importance on academic (B = −0.134, p < 0.01) and societal factors (B = −0.080, p < 0.01) when strategizing on their research agendas. These results suggest that researchers at research universities, perhaps because of their high scientific potential and strong research profiles, are more engaged with their own agendas (and have the power to resist external pressures and pursue them) than researchers working in less research-oriented universities, who may find themselves with few options other than to follow field community and institutional guidelines and to align their behaviors and beliefs accordingly (Ursin et al., 2020). Finally, researchers who are internationally mobile tend to be more ambitious (B = 0.098, p < 0.01) and divergent (B = 0.087, p < 0.01), more likely to pursue potentially disruptive research (B = 0.137, p < 0.01), and more willing to engage in research even with limited funding (B = 0.107, p < 0.01). They are also less influenced by their mentors (B = −0.136, p < 0.01) and less prone to shape their research to be society-driven (B = −0.074, p < 0.01). These results align with findings that internationally mobile researchers are more independent, disruptive, and ambitious but are not as engaged with societal research issues (which may partly be due to language, cultural, and other barriers to collaborating with local laymen or understanding localized societal challenges), and that they are not dependent on mentor influences, which may decrease or be lost due to the mobility process (Huang, Daizen, & Kim, 2019; Kuzhabekova & Lee, 2020).

Conclusion

This study suggests a close association between the conceptions of research that researchers hold and their approach to setting their research agendas. The findings indicate that research conceptions are particularly associated with five dimensions of the research agenda strategy: scientific ambition, collaboration, discovery, academia-driven approach, and society-driven approach. Other dimensions influencing research agendas were also associated with research conceptualizations, but to a lesser extent. Only scientific ambition had positive associations with all conceptions of research, indicating that variety of ways of thinking about the meaning of research all lead to research agendas with an underlying focus on gaining scientific recognition, prestige, and authority in a given scientific field. This suggests that scientific ambition, the positional goods associated with it (e.g. prestige, one of the most sought-after commodities in science and academia; Coate & Howson, 2016), and material rewards (e.g. the “cumulative advantage” hypothesis; Kwiek, 2016) continue to be major drivers for researchers within the social stratification that characterizes the current global scientific social system (Kwiek, 2019). This is the case regardless of whether researchers have a dominant conceptualization of research among an overlap of several or a single definite conceptualization of research (Brew, 2001).

Collaboration had a positive association with almost all of the research conceptualization dimensions (non-statistical significance with research as the discovery of truth). The only negative association was with the concept of misconceptions about research, which can be explained by the fact that it is difficult for a researcher with these misconceptions to collaborate with others, and such a researcher is unlikely to be invited to collaborate on research projects and agendas set by others. There are two main reasons for this. First, misconceptions of research underlines the preconceived ideas that a researcher brings to the research process, which undermine the researcher's expected neutrality and impartiality concerning a research object. Starting a research project with such preconceived ideas is more akin to a political or opinionated view about a research object than to a more ethically neutral research inquiry. Researcher biases are known to jeopardize the trustworthiness and the credibility of the research process and are therefore not acceptable to most of the research community (Jorgensen, et al., 2016; Joseph & Baldwin, 2000). Researchers’ biases also raise ethical research issues, lead to pseudo-scientific findings, and are sometimes related to politically and economically sponsored research, which has caused substantial damage to the image of science, research, and researchers (Nestle, 2016). Second, two of the items of the misconceptions about research dimension, i.e. “If followed correctly, research procedures will always yield positive results” and “for an activity to be called ‘research,’ it must involve experimentation,” highlight a somewhat positivistic but highly rigid view of research processes that would exclude specific types of quantitative research and all qualitative research. This is not attuned with the evolution of contemporary research towards multidisciplinarity, the use of multiple theoretical and methodological paradigms, and nuanced forms of engaging in research processes while following legitimized values and norms of research conduct by relevant scientific communities (Corry, Porter, & McKenna, 2019).

Similar to collaboration, almost all of the conceptions of research have statistically significant associations with discovery—that is, one's willingness to research topics that are riskier but have greater impact potential (no statistical significance was found with research viewed as re-search). In the same vein as collaboration, all of the associations are positively associated with discovery except misconceptions about research. For the reasons mentioned above, this is expected because if one begins research with a preconceived idea, the findings are likely to conform to an initial expectation about what the results will be. Furthermore, even if the purpose of the research is to achieve breakthroughs and innovative thinking, the theoretical and methodological rigidity associated with a high score on misconceptions about research will prevent major findings, as such rigidity is not attuned to the conceptual, methodological, and analytical needs of contemporary science and research breakthroughs (Nairn, 2019).

The relationship between the dimensions of the CoRI and academia-driven approach is statistically significant in all dimensions except research as an insightful process. The statistically significant associations are positive except the association with research as the discovery of truth, which is negative. This may be related to the attitudes of researchers who hold this conception of research (e.g. presenting research impersonally, as if the researcher was not part of the research process; Brew, 2001), which makes them less influenced by institutional pressures and directives from the scientific community and the organization where they work. Contrarily, researchers more influenced by other conceptualizations of research may feel more motivated by institutionally driven pressures and rewards (such as engaging in participatory research that universities push as part of their research and service missions) and more supported in their research activities (even if they are based on misconceptions). The different signs of the statistical effects concerning academia (including the non-significance of one conception) may point toward tension between the research agenda being driven by researchers’ own interests and the matter of personal choice (Kuhn, 2012) and the need to adapt, conform, and adjust research agendas in the face of disciplinary, national, and institutional policies and incentives (Horta & Santos, 2020).

Finally, society-driven agendas were positively associated with misconceptions about research, which might reflect the role of the researcher as an expert in a power relation with non-expert laypersons even when the researcher's expertise is based on potentially biased scientific premises and beliefs. Society-driven agendas were also positively associated with problem-solving, which reflects the interaction with communities enabling researchers to contribute to solving particular social challenges, and with re-research, which reflects the need to constantly revisit societal challenges as they and the knowledge base co-evolve. However, perhaps related to the more applied nature of society-driven research, there were negative associations between society-driven research and both research as the discovery of truth and research as an insightful process. The explanation for these negative associations may involve the positioning of the researcher as one almost absent from awareness and simultaneously involved in a cognitive process focused more on understanding than on providing an applied solution for a specific problem (Brew, 2001). Such research may have relatively low academic interest (not challenging enough for example) despite its practical importance for the community. This is consistent with the “layer conception” proposed by Brew (2001), in which the researcher is interested and concerned with uncovering what lies beneath the reality and through this discovery process eventually provides a better explanation or creates a new paradigm for explaining this reality (Brew et al., 2016). This reflective, abstract, and theoretically driven type of research conception is not consonant with more applied research or with collaborative engagement with laypeople.

Descriptive statistics.

Quantitative VariablesMSD
MDRAI-R dimensions (Dependent variables)Scientific Ambition5.0730.946
Divergence5.0670.918
Collaboration5.1890.826
Mentor Influence2.9061.407
TTLF4.2101.339
Discovery5.5050.922
Academia Driven4.0311.040
Society Driven4.0661.121
CoRI dimensionsTruth-seeking, research as3.8720.982
Misconceptions about research2.6580.949
Problem-solving, research as3.8040.728
Re-research, research as3.5430.743
Insightful process, research as4.3020.530
Control VariablesAge50.75112.034
Years Since PhD18.12912.533
Qualitative VariablesN%
Gender
  Male5,69166.52%
  Female2,86433.47%
Field of Science (FoS)
  Natural & Agricultural Sciences2,49929.21%
  Engineering and Technology1,76120.58%
  Medical and Health Sciences1,98723.23%
  Social Sciences2,04923.95%
  Humanities2593.02%
Research University (top 500)
  Yes1,83821.48%
  No6,71778.51%
Career internationalization
  Yes6,42375.08%
  No2,13224.92%

j.jdis-2020-0032.apptab.001.w2aab3b7c31b1b6b1ab2b3ab3Aa

Strongly disagreeDisagreeNeither agree nor disagreeAgreeStrongly agreeN/A
Solving1The main purpose of research is to identify problems that need to be solved.
Truth1Research is fundamentally about finding out the truth.
Misc3Research is about collecting data back your argument.
Misc1If followed correctly, research procedures will always yield positive results.
Insight3Research extends current concepts to obtain a deeper understanding.
Re1Research means looking for what previous research has failed to uncover.
Solving3Research is about finding solutions to problems.
Re3Research is a systematic investigation to find out if there are facts that were left out by previous researchers.
Insight1Research means an in-depth study of a particular topic.
Truth3Research is done in order to determine the truth about something.
Re4Research means finding out more information about something previously researched.
Re2Research is there to challenge research that has been done before.
Misc2Good research specifically gathers data that will support the researcher's preconceived ideas.
Insight4In answering or understanding something, new ideas present themselves for further investigation.
Insight2Research stimulates further interest or work in a particular topic.
Truth2Research is about revealing the truth.
Misc4For some activity to be called “research” it must involve experimentation.
Solving4Research means collecting data to help solve a particular problem.
Truth4Research is a process for establishing what is true about something.
Solving2Research is basically about solving problems.

Effects of conceptions of research on research agenda setting.

AmbitionDivergenceCollabMentorTTLFDiscoveryAcademiaSociety
Truth0.069*** (0.011)−0.034*** (0.011)−0.008 (0.010)0.021 (0.017)−0.025 (0.016)0.048*** (0.011)−0.026** (0.012)−0.114*** (0.013)
Misconceptions0.056*** (0.013)0.014 (0.013)−0.026** (0.012)0.277*** (0.020)0.078*** (0.019)−0.040*** (0.013)0.165*** (0.014)0.150*** (0.015)
Problem-solving0.064*** (0.016)0.157*** (0.016)0.127*** (0.015)0.034 (0.025)−0.044* (0.024)0.068*** (0.016)0.113*** (0.018)0.310*** (0.019)
Re-research0.104*** (0.016)0.025 (0.016)0.029** (0.014)0.087*** (0.024)0.017 (0.023)−0.020 (0.016)0.085*** (0.017)0.030* (0.018)
Insightful process0.258*** (0.021)0.118*** (0.021)0.241*** (0.019)−0.127*** (0.032)0.085*** (0.030)0.312*** (0.021)−0.030 (0.023)−0.060** (0.024)
Gender (Male)0.091*** (0.022)−0.010 (0.022)0.030 (0.019)0.034 (0.033)0.237*** (0.032)0.101*** (0.022)−0.172*** (0.024)−0.121*** (0.025)
Age−0.020*** (0.002)−0.007*** (0.002)−0.002* (0.001)−0.006** (0.002)0.022*** (0.002)0.001 (0.002)0.000 (0.002)0.016*** (0.002)
Time since PhD0.010*** (0.002)−0.002 (0.002)0.004*** (0.001)−0.024*** (0.002)−0.005** (0.002)0.005*** (0.002)−0.016*** (0.002)−0.021*** (0.002)
Research universities (top 500)0.046* (0.026)0.020 (0.026)0.009 (0.023)0.031 (0.039)−0.053 (0.037)0.054** (0.026)−0.134*** (0.028)−0.080*** (0.030)
FOS (Engineering and Technology)−0.034 (0.028)0.157*** (0.029)−0.078*** (0.025)0.021 (0.043)0.046 (0.041)0.129*** (0.029)0.072** (0.031)0.444*** (0.032)
FOS (Medical and Health sciences)0.075*** (0.028)0.082*** (0.028)0.140*** (0.025)0.142*** (0.043)−0.120*** (0.041)0.015 (0.028)0.154*** (0.031)0.389*** (0.032)
FOS (Social sciences)0.089*** (0.028)−0.061** (0.028)−0.010 (0.025)−0.002 (0.043)0.488*** (0.041)0.067** (0.028)−0.172*** (0.031)0.628*** (0.032)
FOS (Humanities)0.119** (0.059)0.044 (0.060)−0.229*** (0.053)−0.231** (0.090)0.743*** (0.086)0.245*** (0.060)−0.355*** (0.064)0.398*** (0.068)
Career internationalization0.098*** (0.024)0.087*** (0.024)0.017 (0.022)−0.136*** (0.037)0.107*** (0.035)0.137*** (0.024)0.003 (0.026)−0.074*** (0.028)
Country controlsYesYesYesYesYesYesYesYes
Observations8,5548,5558,5547,9208,5518,5548,5548,551
R-squared0.1470.0790.1080.1720.1030.0890.1630.206

j.jdis-2020-0032.apptab.002.w2aab3b7c31b1b6b1ab2b3b1b5Aa

Completely disagreeStrongly disagreeDisagreeNeither agree nor disagreeAgreeStrongly agreeCompletely agreeN/A
A1I aim to one day be one of the most respected experts in my field.
A2Being a highly regarded expert is one of my career goals.
A3I aim to be recognized by my peers.
A5I feel the need to constantly publish new and interesting papers.
A6I am constantly striving to publish new papers.
A7I am driven to publish papers.
DV1I look forward to diversifying into other fields.
DV2I would be interested in pursuing research in other fields.
DV4I would like to publish in different fields.
DV5I enjoy multi-disciplinary research more than single-disciplinary research.
DV6Multi-disciplinary research is more interesting than single-disciplinary research.
DV8I prefer to work with multi-disciplinary rather than single-disciplinary teams.
COL2My publications are enhanced by collaboration with other authors.
COL4I often seek peers with whom I can collaborate on publications.
COL5I enjoy conducting collaborative research with my peers.
COL7My peers often seek to collaborate with me in their publications.
COL8I am often invited to collaborate with my peers.
COL12I am frequently invited to participate in research collaborations due to my reputation.
M2Part of my work is largely due to my PhD mentor.
M3My research choices are highly influenced by my PhD mentor's opinion.
M4My PhD mentor is responsible for a large part of my work.
M6My PhD mentor largely determines my research topics.
TTLF1Limited funding does not constrain my choice of topic.
TTLF2Highly limited funding does not constrain my choice of topic.
TTLF3The availability of research funding for a certain topic does not influence my decision to conduct research on that topic.
TTLF4I am not discouraged by the lack of funding on a certain topic.
D2I would rather conduct revolutionary research with little chance of success than replicate research with a high probability of success.
D3I prefer “innovative” research to “safe” research, even when the odds of success are much lower.
D4I would rather engage in new research endeavors, even when success is unlikely, than safe research that contributes little to the field.
D9I am driven by innovative research.
O1My choice of topics is determined by my field community.
O9I often decide my research agenda in collaboration with my field community.
O6I adjust my research agenda based on my institution's demands.
O7My research agenda is aligned with my institution's research strategies.
S1I decide my research topic based on societal challenges.
S4Societal challenges drive my research choices.
S5I often strive to engage in issues that address societal challenges.
S2I choose my research topics based on my interactions with my non-academic peers.
S3I consider my research topics myself, but this consideration often occurs after I hear what my non-academic peers have to say about these topics.
S6I consider the opinions of my non-academic peers when I choose my research topics.

Abramo, G., D’Angelo, C.A., & Costa, F.D. (2018). The effects of gender, age, and academic rank on research diversification. Scientometrics, 114(2), 373–387.AbramoG.D’AngeloC.A.CostaF.D.2018The effects of gender, age, and academic rank on research diversificationScientometrics114237338710.1007/s11192-017-2529-1Search in Google Scholar

Becher, T., & Trowler, P. (2001). Academic tribes and territories: Intellectual enquiry and the culture of disciplines. Buckingham: Open University Press.BecherT.TrowlerP.2001Academic tribes and territories: Intellectual enquiry and the culture of disciplinesBuckinghamOpen University PressSearch in Google Scholar

Bentley, P.J. (2014). Cross-country differences in publishing productivity of academics in research universities. Scientometrics, 102, 865–883.BentleyP.J.2014Cross-country differences in publishing productivity of academics in research universitiesScientometrics10286588310.1007/s11192-014-1430-4Search in Google Scholar

Bourdieu, P. (1999). The specificity of the scientific field. The Science Studies Reader. Ed. Biagioli, M. New York: Routledge, 31–50.BourdieuP.1999The specificity of the scientific fieldThe Science Studies ReaderEd.BiagioliM.New YorkRoutledge3150Search in Google Scholar

Bozeman, B., & Gaughan, M. (2011). How do men and women differ in research collaborations? An analysis of the collaborative motives and strategies of academic researchers. Research Policy, 40(10), 1393–1402.BozemanB.GaughanM.2011How do men and women differ in research collaborations? An analysis of the collaborative motives and strategies of academic researchersResearch Policy40101393140210.1016/j.respol.2011.07.002Search in Google Scholar

Brew, A. (2001). Conceptions of research: A phenomenographic study. Studies in Higher Education, 26, 271–285.BrewA.2001Conceptions of research: A phenomenographic studyStudies in Higher Education2627128510.4324/9780203464045_chapter_13Search in Google Scholar

Brew, A., Boud, D., Namgung, S.U., Lucas, L., & Crawford, K. (2016). Research productivity and academics’ conceptions of research. Higher Education, 71, 681–697.BrewA.BoudD.NamgungS.U.LucasL.CrawfordK.2016Research productivity and academics’ conceptions of researchHigher Education7168169710.1007/s10734-015-9930-6Search in Google Scholar

Coate, K., & Howson, C.K. (2016). Indicators of esteem: Gender and prestige in academic work. British Journal of Sociology of Education, 37(4), 567–585.CoateK.HowsonC.K.2016Indicators of esteem: Gender and prestige in academic workBritish Journal of Sociology of Education37456758510.1080/01425692.2014.955082Search in Google Scholar

Corry, M., Porter, S., & McKenna, H. (2019). The redundancy of positivism as a paradigm for nursing research. Nursing Philosophy, 20(1), e12230.CorryM.PorterS.McKennaH.2019The redundancy of positivism as a paradigm for nursing researchNursing Philosophy201e1223010.1111/nup.1223030431226Search in Google Scholar

Ebadi, A., & Schiffauerova, A. (2015). How to become an important player in scientific collaboration networks? Journal of Informetrics, 9(4), 809–825.EbadiA.SchiffauerovaA.2015How to become an important player in scientific collaboration networks?Journal of Informetrics9480982510.1016/j.joi.2015.08.002Search in Google Scholar

Foster, J.G., Rzhetsky, A., & Evans, J.A. (2015). Tradition and innovation in scientists’ research strategies. American Sociological Review, 80(5), 875–908.FosterJ.G.RzhetskyA.EvansJ.A.2015Tradition and innovation in scientists’ research strategiesAmerican Sociological Review80587590810.1177/0003122415601618Search in Google Scholar

Fuller, S. (2012). Social epistemology: A quarter-century itinerary. Social Epistemology, 26, 267–283.FullerS.2012Social epistemology: A quarter-century itinerarySocial Epistemology2626728310.1080/02691728.2012.714415Search in Google Scholar

Gaskin, J. (2016). Stats Tool Package. Retrieved from http://statwiki.kolobkreations.comGaskinJ.2016Stats Tool PackageRetrieved from http://statwiki.kolobkreations.comSearch in Google Scholar

Gaughan, M. (2009). Using the curriculum vitae for policy research: An evaluation of National Institutes of Health center and training support on career trajectories. Research Evaluation, 18(2), 117–124.GaughanM.2009Using the curriculum vitae for policy research: An evaluation of National Institutes of Health center and training support on career trajectoriesResearch Evaluation18211712410.3152/095820209X441781Search in Google Scholar

Gorman, S.E., & Gorman, J.M. (2017). Denying to the grave: Why we ignore the facts that will save us. Oxford: Oxford University Press.GormanS.E.GormanJ.M.2017Denying to the grave: Why we ignore the facts that will save usOxfordOxford University PressSearch in Google Scholar

Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2007). Multivariate data analysis. New York: McGraw Hill Publishing.HairJ.F.BlackW.C.BabinB.J.AndersonR.E.TathamR.L.2007Multivariate data analysisNew YorkMcGraw Hill PublishingSearch in Google Scholar

Hemmings, B. (2012). Sources of research confidence for early career academics: A qualitative study. Higher Education Research & Development, 31(2), 171–184.HemmingsB.2012Sources of research confidence for early career academics: A qualitative studyHigher Education Research & Development31217118410.1080/07294360.2011.559198Search in Google Scholar

Hoolohan, C., McLachlan, C., & Larkin, A. (2019). ‘Aha’ moments in the water-energy-food nexus: A new morphological scenario method to accelerate sustainable transformation. Technological Forecasting and Social Change, 148, 119712HoolohanC.McLachlanC.LarkinA.2019‘Aha’ moments in the water-energy-food nexus: A new morphological scenario method to accelerate sustainable transformationTechnological Forecasting and Social Change14811971210.1016/j.techfore.2019.119712Search in Google Scholar

Horta, H., Jung, J., & Santos, J.M. (2019). Mobility and research performance of academics in city-based higher education systems. Higher Education Policy. doi:10.1057/s41307-019-00173-xHortaH.JungJ.SantosJ.M.2019Mobility and research performance of academics in city-based higher education systemsHigher Education Policy10.1057/s41307-019-00173-xOpen DOISearch in Google Scholar

Horta, H., & Santos, J.M. (2016). An instrument to measure individuals’ research agenda setting: The multi-dimensional research agendas inventory. Scientometrics, 108(3), 1243–1265. doi:10.1007/s11192-016-2012-4HortaH.SantosJ.M.2016An instrument to measure individuals’ research agenda setting: The multi-dimensional research agendas inventoryScientometrics10831243126510.1007/s11192-016-2012-4Open DOISearch in Google Scholar

Horta, H., & Santos, J.M. (2019a). Organisational factors and academic research agendas: An analysis of academics in the social sciences. Studies in Higher Education. doi:10.1080/03075079.2019.1612351HortaH.SantosJ.M.2019aOrganisational factors and academic research agendas: An analysis of academics in the social sciencesStudies in Higher Education10.1080/03075079.2019.1612351Open DOISearch in Google Scholar

Horta, H., & Santos, J.M. (2019b). The development of a new instrument to measure research agendas (poster). ISSI 2019, Rome, Italy.HortaH.SantosJ.M.2019bThe development of a new instrument to measure research agendas (poster)ISSI 2019Rome, ItalySearch in Google Scholar

Horta, H. & Santos, J.M. (2020) The multidimensional research agendas inventory—revised (MDRAI-R): Factors shaping researchers’ research agendas in all fields of knowledge. Quantitative Science Studies, 1(1), 60–93.HortaH.SantosJ.M.2020The multidimensional research agendas inventory—revised (MDRAI-R): Factors shaping researchers’ research agendas in all fields of knowledgeQuantitative Science Studies11609310.1162/qss_a_00017Search in Google Scholar

Huang, F., Daizen, T., & Kim, Y. (2019). Challenges facing international faculty at Japanese universities: Main findings from the 2017 national survey. International Journal of Educational Development, 71, 102103.HuangF.DaizenT.KimY.2019Challenges facing international faculty at Japanese universities: Main findings from the 2017 national surveyInternational Journal of Educational Development7110210310.1016/j.ijedudev.2019.102103Search in Google Scholar

Jaeger, A.J., Hudson, T.D., Pasque, P.A., & Ampaw, F.D. (2017). Understanding how lifelong learning shapes the career trajectories of women with STEM doctorates: The life experiences and role negotiations (LEARN) model. The Review of Higher Education, 40(4), 477–507.JaegerA.J.HudsonT.D.PasqueP.A.AmpawF.D.2017Understanding how lifelong learning shapes the career trajectories of women with STEM doctorates: The life experiences and role negotiations (LEARN) modelThe Review of Higher Education40447750710.1353/rhe.2017.0019Search in Google Scholar

Jorgensen, M., Dyba, T., Liestol, K., & Sjoberg, D.I.K. (2016). Incorrect results in software engineering experiments: How to improve research practices. Journal of Systems and Software, 116, 133–145.JorgensenM.DybaT.LiestolK.SjobergD.I.K.2016Incorrect results in software engineering experiments: How to improve research practicesJournal of Systems and Software11613314510.1016/j.jss.2015.03.065Search in Google Scholar

Joseph, J. & Baldwin, S. (2000). Four editorial proposals to improve social sciences research and publication. International Journal of Risk and Safety in Medicine, 13(2,3), 109–116.JosephJ.BaldwinS.2000Four editorial proposals to improve social sciences research and publicationInternational Journal of Risk and Safety in Medicine132,3109116Search in Google Scholar

Kaiser, A. & Leiner, L. (2012). Collaborate with practitioners: But beware of collaborative research. Journal of Management Inquiry, 21(1), 14–28.KaiserA.LeinerL.2012Collaborate with practitioners: But beware of collaborative researchJournal of Management Inquiry211142810.1177/1056492611411923Search in Google Scholar

Kuhn, T.S. (2012). The structure of scientific revolutions. Chicago: University of Chicago Press.KuhnT.S.2012The structure of scientific revolutionsChicagoUniversity of Chicago Press10.7208/chicago/9780226458144.001.0001Search in Google Scholar

Kuzhabekova, A., & Lee, J.T. (2020). Internationalization and local research capacity strengthening: Factors affecting knowledge sharing between international and local faculty in Kazakhstan. European Education. doi:10.1080/10564934.2020.1723422KuzhabekovaA.LeeJ.T.2020Internationalization and local research capacity strengthening: Factors affecting knowledge sharing between international and local faculty in KazakhstanEuropean Education10.1080/10564934.2020.1723422Open DOISearch in Google Scholar

Kwiek, M. (2019). Changing European academics: A comparative study of social stratification, work patterns and research productivity. Abingdon: Routledge.KwiekM.2019Changing European academics: A comparative study of social stratification, work patterns and research productivityAbingdonRoutledgeSearch in Google Scholar

Kwiek, M. (2016). The European research elite: A cross-national study of highly productive academics in 11 countries. Higher Education, 71, 379–397.KwiekM.2016The European research elite: A cross-national study of highly productive academics in 11 countriesHigher Education7137939710.1007/s10734-015-9910-xSearch in Google Scholar

Latour, B., & Woolgar, S. (2013). Laboratory life: The construction of scientific facts. Princeton: Princeton University Press.LatourB.WoolgarS.2013Laboratory life: The construction of scientific factsPrincetonPrinceton University Press10.2307/j.ctt32bbxcSearch in Google Scholar

Lyall, C. (2019). Being an interdisciplinary academic: How institutions shape university careers. Cham: Palgrave.LyallC.2019Being an interdisciplinary academic: How institutions shape university careersChamPalgrave10.1007/978-3-030-18659-3Search in Google Scholar

Meyer, J.H., Shanahan, M.P., & Laugksch, R.C. (2005). Students’ conceptions of research. I: A qualitative and quantitative analysis. Scandinavian Journal of Educational Research, 49(3), 225–244.MeyerJ.H.ShanahanM.P.LaugkschR.C.2005Students’ conceptions of research. I: A qualitative and quantitative analysisScandinavian Journal of Educational Research49322524410.1080/00313830500109535Search in Google Scholar

Meyer, J.H., Shanahan, M.P., & Laugksch, R.C. (2007). Students’ conceptions of research. 2: An exploration of contrasting patterns of variation. Scandinavian Journal of Educational Research, 51(4), 415–433.MeyerJ.H.ShanahanM.P.LaugkschR.C.2007Students’ conceptions of research. 2: An exploration of contrasting patterns of variationScandinavian Journal of Educational Research51441543310.1080/00313830701485627Search in Google Scholar

Milgram, S. (1974). Obedience to authority: An experimental view. London: Tavistock publications.MilgramS.1974Obedience to authority: An experimental viewLondonTavistock publicationsSearch in Google Scholar

Nairn, S. (2019). Research paradigms and the politics of nursing knowledge: A reflective discussion. Nursing Philosophy, 20(4), e12260.NairnS.2019Research paradigms and the politics of nursing knowledge: A reflective discussionNursing Philosophy204e1226010.1111/nup.1226031314182Search in Google Scholar

Nestle, M. (2016). Corporate funding of food and nutrition research: Science or marketing? JAMA Internal Medicine, 176(1), 13–14. doi:10.1001/jamainternmed.2015.6667NestleM.2016Corporate funding of food and nutrition research: Science or marketing?JAMA Internal Medicine1761131410.1001/jamainternmed.2015.666726595855Open DOISearch in Google Scholar

Niiniluoto, I. (2020). Social aspect of scientific knowledge. Synthese, 197, 447–468.NiiniluotoI.2020Social aspect of scientific knowledgeSynthese19744746810.1007/s11229-018-1868-7Search in Google Scholar

Oleksiyenko, A., & Ruan, N. (2019). Intellectual leadership and academic communities: Issues for discussion and research. Higher Education Quarterly, 73(4), 406–418.OleksiyenkoA.RuanN.2019Intellectual leadership and academic communities: Issues for discussion and researchHigher Education Quarterly73440641810.1111/hequ.12199Search in Google Scholar

Pearson, M., & Brew, A. (2002). Research training and supervision development. Studies in Higher Education, 27, 135–150.PearsonM.BrewA.2002Research training and supervision developmentStudies in Higher Education2713515010.1080/03075070220119986cSearch in Google Scholar

Popper, K. (2005). The logic of scientific discovery. New York: Routledge.PopperK.2005The logic of scientific discoveryNew YorkRoutledge10.4324/9780203994627Search in Google Scholar

Ramos, A.M.G., Palacin, F.F., & Márquez, M.M. (2015). Do men and women perform academic work differently? Tertiary Education and Management, 21(4), 263–276.RamosA.M.G.PalacinF.F.MárquezM.M.2015Do men and women perform academic work differently?Tertiary Education and Management21426327610.1080/13583883.2015.1065904Search in Google Scholar

Santos, J.M., & Horta, H. (2018). The research agenda setting of higher education researchers. Higher Education, 76(4), 649–668. doi:10.1007/s10734-018-0230-9SantosJ.M.HortaH.2018The research agenda setting of higher education researchersHigher Education76464966810.1007/s10734-018-0230-9Open DOISearch in Google Scholar

Stehr, N., & Grundmann, R. (2011). Experts: The knowledge and power of expertise. Abingdon: Routledge.StehrN.GrundmannR.2011Experts: The knowledge and power of expertiseAbingdonRoutledge10.4324/9780203829646Search in Google Scholar

Ursin, J., Vahasantanen, K., McAlpine, L., & Hokka, P. (2020). Emotionally loaded identity and agency in Finnish academic work. Journal of Further and Higher Education, 44(3), 311–325.UrsinJ.VahasantanenK.McAlpineL.HokkaP.2020Emotionally loaded identity and agency in Finnish academic workJournal of Further and Higher Education44331132510.1080/0309877X.2018.1541971Search in Google Scholar

Vaesen, K., & Katzav, J. (2017). How much would each researcher receive if competitive government research funding were distributed equally among researchers? PLoS ONE, 12(9), e0183967. https://doi.org/10.1371/journal.pone.0183967VaesenK.KatzavJ.2017How much would each researcher receive if competitive government research funding were distributed equally among researchers?PLoS ONE129e0183967https://doi.org/10.1371/journal.pone.018396710.1371/journal.pone.0183967559085828886054Search in Google Scholar

Wynn, J. (2017). Citizen science in the digital age: Rhetoric, science, and public engagement. Tuscaloosa: The University of Alabama Press.WynnJ.2017Citizen science in the digital age: Rhetoric, science, and public engagementTuscaloosaThe University of Alabama PressSearch in Google Scholar

Ying, Q.F., Venkatramanan, S., & Chiu, D.M. (2015). Modeling and analysis of scholar mobility on scientific landscape. WWW ’15 Companion. In Proceedings of the 24th International Conference on World Wide Web: 609–614. ACM.YingQ.F.VenkatramananS.ChiuD.M.2015Modeling and analysis of scholar mobility on scientific landscape. WWW ’15 CompanionInProceedings of the 24th International Conference on World Wide Web: 609–614ACMSearch in Google Scholar

Young, M. (2015). Competitive funding, citation regimes, and the diminishment of breakthrough research. Higher Education, 69, 421–434.YoungM.2015Competitive funding, citation regimes, and the diminishment of breakthrough researchHigher Education6942143410.1007/s10734-014-9783-4Search in Google Scholar

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