Erin E Leahey

Interests

Research

science and innovation, scientific careers

Teaching

research design; science, knowledge, and innovation; quantitative analysis & reasoning

Courses

Scholarly Contributions

Chapters

• Leahey, E. E., & Blume, A. (2017). Elucidating the Gender Divide in Patenting Activity. In Gender and Entrepreneurial Activity. Edward Elgar Publishing.
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  Leahey, Erin, and Amelia Blume (2017). “Elucidating the Gender Divide in Patenting Activity.” Chapter 7 (pp. 151-167) in Al Link (ed.) Gender and Entrepreneurial Activity. Edward Elgar Publishing.
• Leahey, E. E., & McBee, D. (2016). “New Directions in Interdisciplinary Training: Trials and Tribulations”. In Investigating Interdisciplinary Research: Theory and Practice across Disciplines.. Rutgers, NJ: Rutgers University Press.
• Barringer, S., Eliason, S., & Leahey, E. E. (2013). A History of Causal Analysis in the Social Sciences. In Handbook of Causal Analysis for Social Research. Springer.
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  Barringer, Sondra, Scott R. Eliason, and Erin Leahey (2013). "A History of Causal Analysis in the Social Sciences." Chapter in the Handbook of Causal Analysis for Social Research edited by Stephen L. Morgan. Springer, pp. 9-26.

Journals/Publications

• Bratt, S., Leahey, E., Gomez, C., Lee, J., Kwon, Y., & Lassiter, C. (2024). Developing a Text-Based Measure of Humility in Inquiry Using Computational Grounded Theory. Proceedings of the Association for Information Science and Technology, 61(1). doi:10.1002/pra2.1119
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  We describe a project in which we develop a text-based measure of HI in the context of scholarly communication using corpora of scientific publications. The data and analytic approach we use will circumvent known concerns with self-reported data on humility levels and will be calculable on a large scale. We use a computational grounded theory approach to develop a text-based measure of HI. We draw from an annotated corpus of scientific articles in economics, psychology, and sociology (2010–2023), generating three supra-dimensions of HI (Epistemic, Rhetorical, and Transparent) and several novel sub-codes of HI. We present our initial analysis with a focus on the three dimensions of HI derived from a computational grounded theory approach. The text-based measure helps us better understand how contextual factors shape HI and contribute to mixed methods in information science research.
• Leahey, E. E., Lee, J., & Funk, R. J. (2023). What Types of Novelty are most Disruptive?. American Sociological Review.
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  This is the first full paper to emanate from my 2018-2021 collaborative NSF grant with my Co-I Russ Funk, Assistant Professor at the Carlson School of Management at the University of Minnesota. I presented it to a few audiences between July 2020 and January 2021. Jina Lee is one of the RAs on the project and a critical contributor to this paper.
• Leahey, E. E., Lee, J., & Funk, R. J. (2023). What Types of Novelty are most Disruptive?. American Sociological Review, 88(3), 562–597.
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  This paper was supported by a NSF grant to me and my Co-PI Russell Funk at the Carlton School of Management at the University of Minnesota. My PhD student Jina Lee was RA on the project and a coauthor.
• Park, M., Leahey, E., & Funk, R. (2023). Papers and patents are becoming less disruptive over time. Nature, 613(7942). doi:10.1038/s41586-022-05543-x
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  Theories of scientific and technological change view discovery and invention as endogenous processes1,2, wherein previous accumulated knowledge enables future progress by allowing researchers to, in Newton’s words, ‘stand on the shoulders of giants’3–7. Recent decades have witnessed exponential growth in the volume of new scientific and technological knowledge, thereby creating conditions that should be ripe for major advances8,9. Yet contrary to this view, studies suggest that progress is slowing in several major fields10,11. Here, we analyse these claims at scale across six decades, using data on 45 million papers and 3.9 million patents from six large-scale datasets, together with a new quantitative metric—the CD index12—that characterizes how papers and patents change networks of citations in science and technology. We find that papers and patents are increasingly less likely to break with the past in ways that push science and technology in new directions. This pattern holds universally across fields and is robust across multiple different citation- and text-based metrics1,13–17. Subsequently, we link this decline in disruptiveness to a narrowing in the use of previous knowledge, allowing us to reconcile the patterns we observe with the ‘shoulders of giants’ view. We find that the observed declines are unlikely to be driven by changes in the quality of published science, citation practices or field-specific factors. Overall, our results suggest that slowing rates of disruption may reflect a fundamental shift in the nature of science and technology.
• Leahey, E., Lee, J., & Seo, M. (2022). Who Deserves Protection? How Naming Potential Beneficiaries Influences COVID-19 Vaccine Intentions. Socius: Sociological Research for a Dynamic World, 8, 237802312210824. doi:10.1177/23780231221082422
• Park, M., Leahey, E. E., & Funk, R. J. (2020). Dynamics of Disruption in Science and Technology. TBD.
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  This is another paper emanating from the collaborative NSF grant with Co-I Russ Funk. Mike Park is an international graduate student at U Minnesota. We analyze all Web of Science articles and all US Patents over a 50 years period to understand whether and how scientific work is becoming less disruptive. This paper won a Best Paper award at the Academy of Management in summer 2021. We submitted the paper to Science, but it was rejected. We are now revising and deciding where to send it next.
• Wu, L., Kittur, A., Youn, H., Milojevic, S., Leahey, E., Fiore, S., & Ahn, Y. (2022). Metrics and mechanisms: Measuring the unmeasurable in the science of science. Journal of Informetrics, 16(2). doi:10.1016/j.joi.2022.101290
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  What science does, what science could do, and how to make science work? If we want to know the answers to these questions, we need to be able to uncover the mechanisms of science, going beyond metrics that are easily collectible and quantifiable. In this perspective piece, we link metrics to mechanisms by demonstrating how emerging metrics of science not only offer complementaries to existing ones, but also shed light on the hidden structure and mechanisms of science. Based on fundamental properties of science, we classify existing theories and findings into: hot and cold science referring to attention shift between scientific fields, fast and slow science reflecting productivity of scientists and teams, soft and hard science revealing reproducibility of scientific research. We suggest that interest about mechanisms of science since Derek J. de Solla Price, Robert K. Merton, Eugene Garfield, and many others complement the zeitgeist in pursuing new, complex metrics without understanding the underlying processes. We propose that understanding and modeling the mechanisms of science condition effective development and application of metrics.
• Barringer, S., Leahey, E. E., & Salazar, K. (2020). “What Catalyzes Universities’ Commitment to Interdisciplinary Research?”. Research in Higher Education, 61, 679–705.
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  This is the third published paper to emanate out of my collaborative NSF grant (2015-2019) with former PhD student Sondra Barringer, now at SMU. Karina Salazar was an RA on the project for 3 years, and is a first generation student from South Tucson.Research in Higher Education (JIF 2.2) publishes studies that examine issues pertaining to postsecondary education.
• Hackett, E. J., Leahey, E. E., & Parker, J. N. (2021). “Do Synthesis Centers Synthesize? A Semantic Analysis of Diversity in Research Output”. Research Policy, 48. doi:https://doi.org/10.1016/j.respol.2020.104069
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  Work on this large-scale and computationally intensive analysis began in about 2012! The international team met several times over a period of years at two synthesis centers - NCEAS at UCSB and NesCent at Duke - and collaborated effectively.There are several other authors including: Ismael Rafols, Stephanie Hampton, Ugo Corte, John M. Drake, Bart Penders, Laura Sheble, Niki Vermeulen, Todd Vision.Research Policy (JIF 5.3) is a multi-disciplinary journal devoted to analyzing, understanding and effectively responding to the economic, policy, management, organizational, environmental and other challenges posed by innovation, technology, R&D and science. Edward J. Hackett, Erin Leahey, John N. Parker, Ismael Rafols, Stephanie Hampton, Ugo Corte, John M. Drake, Bart Penders, Laura Sheble, Niki Vermeulen, Todd Vision (2021). “Do Synthesis Centers Synthesize? A Semantic Analysis of Diversity in Research Output.” Research Policy 50(1)
• Leahey, E. E., & Barringer, S. (2020). Universities’ Commitment to Interdisciplinary Research: To What End?. Research Policy.
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  This paper has been published in Research Policy, Research Policy (JIF 5.3) is a multi-disciplinary journal devoted to analyzing, understanding and effectively responding to the economic, policy, management, organizational, environmental and other challenges posed by innovation, technology, R&D and science. The research was funded by a collaborative NSF grant with former PhD student Sondra Barringer (now at SMU).
• Koppman, S., & Leahey, E. (2019). Who moves to the methodological edge? Factors that encourage scientists to use unconventional methods. Research Policy, 48(9).
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  Research Policy (JIF 5.3) is a multi-disciplinary journal devoted to analyzing, understanding and effectively responding to the economic, policy, management, organizational, environmental and other challenges posed by innovation, technology, R&D and science.
• Leahey, E., Barringer, S. N., & Ring-Ramirez, M. (2019). Universities' structural commitment to interdisciplinary research. Scientometrics, 118(3), 891-919.
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  This is the first/foundational paper from our 3 year NSF grant that ended in 2019. Co-I Sondra Barringer earned her PhD from UA in 2013 and is now Assistant Professor at SMU.Scientometrics (JIF 2.9) is concerned with the quantitative features and characteristics of science and scientific research.
• Koppman, S., & Leahey, E. E. (2016). Risk and Reputation: How Professional Classification Signals Drive the Diffusion of New Methods. working paper under revision.
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  This project was funded by the ConfluenCenter at UA; we collected original data, analyzed it, and wrote a paper for submission to ASA and Academy of Management annual meetings. Both were due in early January 2016, and both have been accepted.
• Leahey, E. E., & Koppman, S. (2015). Risk and Reputation: How Professional Classification Signals Drive the Diffusion of New Methods. ASA conference paper.
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  This project was funded by the ConfluenCenter at UA; we collected original data, analyzed it, and wrote a paper for submission to ASA and Academy of Management annual meetings. Both were due in early January 2016, and both have been accepted.
• Leahey, E. E., Nielsen, M. W., Alegria, S., Börjeson, L., Etzkowitz, H., Falk-Krzesinski, H. J., Joshi, A., Smith-Doerr, L., Woolley, A. W., & Schiebinger, L. (2018). The Perks and Perils of Interdisciplinary Research. European Review, 26, S55-S67.
• Leahey, E. E. (2015). From Solo Investigator to Team Scientist: Trends in the Practice and Study of Research Collaboration. Annual Review of Sociology.
• Leahey, E. E., Beckman, C., & Stanko, T. (2009). Prominent but Less Productuve: The Impact of Interdisicplinarity on Scientists' Research. Administrative Science Quarterly.
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  The paper has received a second "revise and resubmit" from Administrative Science Quarterly.
• Leahey, E. E., Beckman, C., & Stanko, T. (2017). Prominent but Less Productive: The Impact of Interdisicplinarity on Scientists' Research. Administrative Science Quarterly.
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  Administrative Science Quarterly (ASQ; JIF 8.3), owned and managed by the Samuel Curtis Johnson Graduate School of Management at Cornell University,is a top-ranked, quarterly, peer-reviewed journal that publishes the best theoretical and empirical papers on organizational studies from dissertations and the evolving, new work of more established scholars, as well as interdisciplinary work in organizational theory, and informative book reviews.
• Leahey, E., Mathias, N., Alegria, S., Börjeson, L., Etzkowitz, H., Falk-Krzesinski, H., Joshi, A., Leahey, E. L., Smith-Doerr, L., Williams Woolley, A., & Schiebinger, L. (2017). Gender diversity leads to better science. Proceedings of the National Academy of Sciences.
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  Nielsen, Mathias W., Sharla Alegria, Love Börjeson, Henry Etzkowitz, Holly J. Falk-Krzesinski, Aparna Joshi, Erin Leahey, Laurel Smith-Doerr, Anita Williams Woolley, and Londa Schiebinger (2017). “Gender diversity leads to better science.” Proceedings of the National Academy of Sciences 114(8): 1740–1742. doi: 10.1073/pnas.1700616114
• Nielsen, M., Alegria, S., Etzkowitz, H., Falk-Krzesinski, H., Joshi, A., Leahey, E., Smith-Doerr, L., Woolley, A., Schiebinger, L., & Börjeson, L. (2017). Correction: Gender diversity leads to better science (Proceedings of the National Academy of Sciences of the United States of America (2017) 114 (1740-1742) DOI: 10.1073/pnas.1700616114). Proceedings of the National Academy of Sciences of the United States of America, 114(13). doi:10.1073/pnas.1703146114
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  Correction for "Opinion: Gender diversity leads to better science," by MathiasWullum Nielsen, Sharla Alegria, Love Börjeson, Henry Etzkowitz, Holly J. Falk-Krzesinski, Aparna Joshi, Erin Leahey, Laurel Smith-Doerr, Anita Williams Woolley, and Londa Schiebinger, which appeared in issue 8, February 21, 2017, of Proc Natl Acad Sci USA (114:1740-1742; 10.1073/pnas.1700616114). The editors note that, due to a printer's error, references 7 and 8 were each inadvertently repeated in the text, in the second and third full paragraphs on page 1741, respectively. The extraneous callouts to references 7 and 8 have now been removed.
• Beckman, C. M., Leahey, E., & Stanko, T. L. (2016). Prominent but Less Productive: The Impact of Interdisciplinarity on Scientists’ Research. Administrative Science Quarterly, 62(1), 105-139. doi:10.1177/0001839216665364
• Leahey, E. E. (2016). From Solo Investigator to Team Scientist: Trends in the Practice and Study of Research Collaboration. Annual Review of Sociology.
• Cain, C. L., Koppman, S., & Leahey, E. (2015). The Joy of Science Disciplinary Diversity in Emotional Accounts. Science, Technology, & Human Values, 40(1), 30-70. doi:10.1177/0162243914537527
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  Science and emotions are typically juxtaposed: science is considered rational and unattached to outcomes, whereas emotions are considered irrational and harmful to science. Ethnographic studies of the daily lives of scientists have problematized this opposition, focusing on the emotional experiences of scientists as they go about their work, but they reveal little about disciplinary differences. We build on these studies by analyzing Citation Classics: accounts about the making of influential science. We document how highly cited scientists retrospectively describe emotional aspects of their research and assess variation in these narratives across six diverse disciplines: Chemistry; Clinical Medicine; Neurobiology; Physics; Plant and Animal Science; and Psychology and Psychiatry. Using correspondence analysis, we develop a multidimensional model to explain disciplinary variation in scientists’ accounts of emotions and link this variation to internal, external, and material aspects of the disciplines. We f...
• Koppman, S., Cain, C., & Leahey, E. E. (2013). The Joy of Science: Disciplinary Diversity in Emotional Accounts. Science, Technology, and Human Values.
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  First two authors were/are graduate students and RAs on the NSF project.
• Cain, C. L., & Leahey, E. (2014). Cultural Correlates of Gender Integration in Science. Gender, Work and Organization, 21(6), 516-530. doi:10.1111/gwao.12052
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  Gender integration within science has been uneven: some fields have integrated women to almost equitable levels, while others remain male-dominated. Explanations for this variation abound, but few are able to assess empirically the relevance of disciplinary cultures in a systematic way. We take up this challenge by analysing accounts of scientific success in fields that integrated women to a large degree (Psychology and the Life Sciences) and fields that did not (Engineering and Physics). We qualitatively assess how the salience of relationships changed over time in these fields. We find that scientists from disciplines that have crossed the threshold whereby women are no longer tokens culturally value informal relationships more than those in which women remain a small numerical minority.
• Leahey, E. E., & Moody, J. (2013). Sociological Innovation through Subfield Integration. Social Currents.
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  Leahey, Erin, and James Moody. Sociological Innovation through Subfield Integration Revise & resubmit.
• Leahey, E., & Moody, J. (2014). Sociological Innovation through Subfield Integration. Social currents, 1(3), 228-256. doi:10.1177/2329496514540131
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  Is domain-spanning beneficial? Can it promote innovation? Classic research on recombinant innovation suggests that domain-spanning fosters the accumulation of diverse information and can thus be a springboard for fresh ideas—most of which emanate from the merger of extant ideas from distinct realms. But domain-spanning is also challenging to produce and to evaluate. Here, the domains of interest are subfields. We focus on subfield spanning in sociology, a topically diverse field whose distinct subfields are still reasonably permeable. To do so, we introduce two measures of subfield integration, one of which uniquely accounts for the novelty of subfield combinations. We find (within the limits of observable data) the costs to be minimal but the rewards substantial: Once published, sociology articles that integrate subfields (especially rarely spanned subfields) garner more citations. We discuss how these results illuminate trends in the discipline of sociology and inform theories of recombinant innovation.
• Leahey, E. E. (2013). No Decline, Just Loss of Dominance: A Prompt to Worry (a bit) and Ask Why. Contemporary Sociology.
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  Book review.Leahey, Erin (2013). No Decline, just Loss of Dominance: A Prompt to Worry (a bit) and Ask Why. Lead review on symposium about Yu Xie and Alexandra Killewald _Is American Science in Decline?_ Harvard University Press 2012. Contemporary Sociology 42(6): 790-92.
• Leahey, E. E., & Cain, C. L. (2013). Straight from the Source: Accounting for Scientific Success. Social Studies of Science, 43(6), 24.
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  Leahey, Erin, and Cindy L. Cain (2013). “Straight from the Source: Accounting for Scientific Success.” Social Studies of Science 43(6): 927-951.This is the first and main paper to result from my NSF grant.
• Leahey, E. E. (2012). Lawyers' Lines of Work: The Role of Specialization in the Income Determination Process. Social Forces.
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  Leahey, Erin, and Laura A. Hunter (2012). “Lawyers’ Lines of Work: The Role of Specialization in the Income Determination Process.” Social Forces 90(4):1101-1132. This paper was published with graduate student Laura Hunter.
• Crockett, J. L., Keith, B., & Leahey, E. (2010). Specialization and promotion in an academic discipline. Research in Social Stratification and Mobility, 28(2), 135-155. doi:10.1016/j.rssm.2009.12.001
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  Abstract What does it take to get tenure in an academic discipline? The receipt of tenure has received less attention in the research literature on scientific careers than other career outcomes. To explain variation in the “risk” of receiving tenure, we theorize that the extent of specialization in scholars’ research programs should improve promotion prospects, especially for men. Using data on sociology PhD recipients in 1972–1976, we construct a measure of research specialization and add it to a traditional attainment model that includes productivity, visibility, and prestige of specialty area(s). We find that a high degree of specialization actually decreases promotion prospects, at least for men.
• Hunter, L. A., & Leahey, E. (2010). Parenting and research productivity: New evidence and methods. Social Studies of Science, 40(3), 433-451. doi:10.1177/0306312709358472
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  To date, studies on how having children affects the research productivity of academics, and whether the effects differ by gender, have had inconsistent findings. Using nuanced measures of parental obligations and linear growth modeling, we analyzed the effects of children on the entire careers of academics in two disciplines — linguistics and sociology — and tested for differential effects by gender. In addition, we modeled not only productivity, but also visibility, another component of scholarly success. Our findings suggest that after the birth a child, productivity growth declines, but more so for women. Thus, children account for part of the gender gap in rates of productivity over time. Children also have an impact on the research visibility of academics, but cannot account for gender differences in visibility.
• Crockett, J. L., Hunter, L. A., & Leahey, E. (2008). Gendered Academic Careers: Specializing for Success?. Social Forces, 86(3), 1273-1309. doi:10.1353/sof.0.0018
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  University of ArizonaIn this article we take a longitudinal perspective to analyze gender differences in academic career attainment. We improve upon prior research both theoretically and methodologically. Theoretically, we incorporate the extent of research specialization as a form of professional capital that potentially improves productivity and visibility, especially for men. Methodologically, we introduce a measure of research specialization and examine how men’s and women’s productivity and visibility unfold over time, rather than examining discrete periods of scholars’ careers. We find that specializing is most beneficial with regard to productivity – that is, it helps scholars publish more. Specialization’s effects on visibility are less general: surprisingly, only women’s visibility seems to benefit from specialization. We discuss these findings and their implications, and suggest avenues for future research on this important and newly recognized form of capital.
• Hunter, L. A., & Leahey, E. (2008). Collaborative Research in Sociology: Trends and Contributing Factors. The American Sociologist, 39(4), 290-306. doi:10.1007/s12108-008-9042-1
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  To what extent do sociologists collaborate? Has this changed over time? What factors contribute to research collaboration among sociologists? To answer these questions, we examine trends in collaboration over a 70 year period and empirically test a variety of explanations for the increase in collaboration that we find. We analyze data collected from a stratified random sample of articles in two leading sociology journals between 1935 and 2005 (n = 1274). Most of our analyses are descriptive and display trends over time. However, we pool the data across all years and estimate logistic regression models to assess the relative contribution of various factors. We find that the importance of geographical location has been waning since the 1950s, although the growth in cross-place collaborations stagnated between 1980 and 2005. We find that quantitative research is more likely to be collaborative, as are projects requiring data collection, though this may change because the collaboration rate among secondary data users is increasing at a faster rate. We find no significant gender differences in rates of collaboration, although male sole-authorship remains the most common form of publication. We also find the institutional prestige of coauthors is typically higher than that of sole-authors. Our results elucidate the extent of collaboration in sociology and reveal how several factors have contributed to this major shift in work organization.
• Leahey, E. (2008). Methodological Memes and Mores: Toward a Sociology of Social Research. Review of Sociology, 34(1), 33-53. doi:10.1146/annurev.soc.34.040507.134731
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  A plethora of scholarly research has been conducted on social science: on its organizational and communicative patterns, on the historical development of research standards, and on the diversity of local research practices. But this body of work on the sociology of social research does not hang together in ways that it could, and should, if knowledge is to accumulate. Contributors hail from various fields, subfields, theoretical perspectives, and methodological bents, and there is no extant subfield to join, legitimate, and reinforce their mutual interests. Thus, the aim of this review is not only to summarize themes, identify gaps, and suggest fruitful avenues for future research, but also to serve as a unifying force for scholars interested in studying social science from a sociological perspective. The sociology of social research, far from being a trite exercise in navel-gazing, is critical for the future viability of sociology, for the discipline's legitimacy and autonomy, and for improving social re...
• Leahey, E. (2008). Overseeing Research Practice: The Case of Data Editing. Science, Technology, & Human Values, 33(5), 605-630. doi:10.1177/0162243907306702
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  This article examines whether and how a particular research practice is overseen and supervised, and by whom. This investigation fills notable gaps in the literature on science, including a lack of emphasis on larger sociopolitical structures, a neglect of regulation, and indifference toward ethics. The author focuses on the oversight of a particular research practice; data editing; which embodies qualities that are intriguing to sociologists of science: invisibility, uncertainty, heterogeneity, and reliance on tacit knowledge. These characteristics pose unique challenges to oversight efforts. An analysis of in-depth interviews with gatekeepers reveals that although the methodological and ethical implications of data editing strategies can be substantial, oversight of such practices falls outside the stages and domains of current gatekeeping activity. These findings serve as the basis for recommendations to ensure data integrity while maintaining the professional autonomy of researchers.
• Leahey, E. E., & Reikowsky, R. C. (2008). Research Specialization and Collaboration Patterns in Sociology. Social Studies of Science, 38(3), 425-440.
• Leahey, E. (2007). Convergence and confidentiality? Limits to the implementation of mixed methodology. Social Science Research, 36(1). doi:10.1016/j.ssresearch.2005.10.003
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  The purpose of this paper is to identify and explain a rather large impediment to the use of mixed method research designs that begin with survey data. Although supplementing quantitative survey analyses with insights derived from qualitative work is increasingly popular, there is also heightened concern about ethical issues in research, particularly the confidentiality of human research subjects. Surprisingly, there has been little discussion about how these two trends intersect, and the extent to which they are compatible. In this paper I argue that because of the important obligation to protect human research subjects' identities (and, to a lesser extent, the proliferation of publicly available datasets), few researchers are actually in a position to implement this type of mixed methodology. Despite their noted advantages over mono-method designs, mixed method designs that start with quantitative data and subsequently supplement it with qualitative insights may not achieve the dominance that many have supposed and desired. © 2005 Elsevier Inc. All rights reserved.
• Leahey, E. (2007). Not by Productivity Alone: How Visibility and Specialization Contribute to Academic Earnings.. American Sociological Review, 72(4), 533-561. doi:10.1177/000312240707200403
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  The popular adage “publish or perish” has long defined individual career strategies as well as scholarly investigations of earnings inequality in academe, as researchers have relied heavily on rese...
• Leahey, E. (2007). The New Political Sociology of Science: Institutions, Networks, and Power. Edited by Scott Frickel and Kelly Moore. Madison: University of Wisconsin Press, 2006. Pp. 487. $60.00.. American Journal of Sociology, 113(1), 262-264. doi:10.1086/520890
• Leahey, E. (2006). Gender Differences in Productivity Research Specialization as a Missing Link. Gender & Society, 20(6), 754-780. doi:10.1177/0891243206293030
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  Since 1984, when Cole and Zuckerman referred to gender differences in productivity among academic scientists as a puzzle, sociologists have sought to explain these differences by incorporating primarily institutional-level factors. In addition to these factors, the author contends that an undertheorized and heretofore unmeasured concept—the extent of research specialization—can also help explain the process by which gender affects research productivity. Although some researchers have examined areas of specialization, the extent of research specialization has been completely neglected in studies of academic careers. Using a probability sample of academics in two disciplines (sociology and linguistics), primary data collection, and simultaneous equation modeling, the author finds that the extent of research specialization is a critical intervening variable: Women specialize less than men and thereby lose out on an important means of increasing their productivity.
• Leahey, E. (2006). Transmitting Tricks of the Trade: Advisors and the Development of Research Knowledge.. Teaching Sociology, 34(2), 93-110. doi:10.1177/0092055x0603400201
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  How is sociological research practice learned? Because much of the tacit knowledge required to succeed in professions such as academia cannot be obtained formally, informal channels of learning—such as interaction with advisors—may be crucial. In this paper I test the extent to which graduate school advisors influence the development of their advisees' research habits, practices, and beliefs. I find that advisors' attitudes and intra-professional standing affect how their advisees view various research practices—both those that are less codified (such as how to deal with anomalous data) and those that are quite standardized (such as statistical significance testing). For the least standardized and most qualitative research practices, such as interpreting qualitative text, I find that students' experiences are more relevant that advisors' attitudes. I discuss these findings by referencing literature in the sociology of science and knowledge and relate my findings to broader knowledge about teaching sociolo...
• Leahey, E. (2005). Alphas and Asterisks: The Development of Statistical Significance Testing Standards in Sociology. Social Forces, 84(1), 1-24. doi:10.1353/sof.2005.0108
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  In this paper, I trace the development of statistical significance testing standards in sociology by analyzing data from articles published in two prestigious sociology journals between 1935 and 2000. I focus on the role of two key elements in the diffusion literature, contagion and rationality, as well as the role of institutional factors. I find that statistical significance testing flourished in the 20th century. Contagion processes and the suitability of significance testing given a study’s data characteristics encourage the diffusion of significance testing, whereas institutional factors such as department prestige and particular editorships help explain growing popularity of the .05 alpha level and use of the “three-star system” of symbolic codes (i.e., *p < = .05, **p < = .01, ***p < = .001).
• Kurzman, C., & Leahey, E. (2004). Intellectuals and Democratization, 1905-1912 and 1989-1996. American Journal of Sociology, 109(4), 937-986. doi:10.1086/378929
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  This article bridges the gap in studies of the social bases of democratization between qualitative studies focused on social groups and quantitative studies focused on national characteristics. Qualitative historical evidence suggests the importance of classes—in particular, the emerging class of intellectuals—in the wave of democratizations in the decade before World War I. Quantitative cross‐national data on a more recent wave of democratizations, from 1989 to 1996, confirm these findings. Models using direct maximum‐likelihood estimation find that the ratio of adults with higher education has a significant positive effect on change in democracy levels, as measured by two longitudinal scales (Polity IV and Polyarchy). Proxies for the working class and the middle class—candidates proposed in previous studies as the social basis of democratization—also have significant effects.
• Leahey, E. (2004). The role of status in evaluating research: The case of data editing. Social Science Research, 33(3). doi:10.1016/j.ssresearch.2003.09.004
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  Cleaning and editing apparently illogical, or seemingly incorrect, data is a ubiquitous research practice. But a lack of formal guidance in this realm of research may promote reliance on colleagues' knowledge and on information from the situation at hand, such as status considerations. To investigate the extent to which status considerations influence sociological research practice, I conducted a survey-based experiment using hypothetical vignettes. A sample of sociologists was asked to respond to a hypothetical vignette depicting a researcher's encounter with apparently messy data and a proposed editing strategy. The vignettes controlled for all variables except one-the status of the hypothetical researcher-and one vignette was randomly assigned to each sociologist. I find that status considerations are relevant to sociological research. Researchers judge the same data cleaning strategy more stringently when a graduate student, rather than a professor, proposes the strategy. Implications of these findings for the objectivity and universality of sociological research practice are discussed. © 2003 Elsevier Inc. All rights reserved.
• Churchill, L., Nelson, D., Henderson, G., King, N., Davis, A., Leahey, E., & Wilfond, B. (2003). Assessing benefits in clinical research: why diversity in benefit assessment can be risky.. IRB, 25(3). doi:10.2307/3564297
• Einaudi, P., Entwisle, B., & Leahey, E. (2003). Diversity in Everyday Research Practice: The Case of Data Editing. Sociological Methods & Research, 32(1), 64-89. doi:10.1177/0049124103253461
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  How should social science researchers deal with data inaccuracies? This article uses Web-based survey data collected from faculty members in three social science disciplines to document variation in views about data editing. Through an analysis of qualitative responses to a hypothetical vignette, the authors demonstrate that a wide range of opinion surrounds the “proper” use of data. Reactions are to some extent contingent on discipline and experience with different types of data and data collection methods. They also depend on characteristics of the data-editing situation—for example, whether the problem is with an independent or dependent variable. Even taking these social and situational factors into account, however, there is still substantial diversity in vignette responses. Normative standards that pervade other aspects of the research process have not yet emerged for data editing.
• Guo, G., & Leahey, E. (2001). Gender Differences in Mathematical Trajectories. Social Forces, 80(2), 713-732. doi:10.1353/sof.2001.0102
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  In this article we test the hypothesis that male students outperform female students in mathematics. Using large national data sets and curvilinear growth models, we examine gender differences in mathematical trajectories from elementaiy school through high school. We analyze subsamples of high-scoring students and also different areas of math, such as reasoning and geometry. Despite relatively equal starting points in elementary school, and relatively equal slopes, we find that boys have a faster rate of acceleration. By the 12th grade, this results in a slight gender difference, which is most pronounced in geometry. Realizing this slight and delayed emergence of gender differences, we qualify the strong conclusions of earlier research, such as Benbow and Stanley's (1980, 1983), which found that large gender differences emerge by junior high school.
• Leahey, E. (2001). A help or a hindrance? The impact of job training on the employment status of disadvantaged women.. Evaluation review, 25(1), 29-54. doi:10.1177/0193841x0102500102
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  The objective of this study is to evaluate whether welfare-sponsored, government-funded job training helps participants improve their employment status. The negligible effects found in prior studies may be due to design limitations or inherent flaws in job training programs and therefore do not necessarily contradict human capital theory. The present study uses longitudinal and representative data, dynamic modeling techniques, an appropriate counterfactual, and important contextual variables to assess the likelihood of obtaining employment for job training participants and nonparticipants. It also describes the types of jobs women obtain by examining wages, industry, occupation, and labor union membership. Whereas some of the results support prior research, the focus is on the unique contributions of this study, which include a differential training effect for full- and part-time workers and a detailed analysis of macro-structural variables, which are rarely included in studies of labor supply.

Proceedings Publications

• Leahey, E. E. (2012, September). Shaping Scientific Work: The Organization of Knowledge Communities. In National Academies of Science: SciSIP PI conference - commissioned paper.
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  Leahey, Erin (2012). “Shaping Scientific Work: The Organization of Knowledge Communities.” Paper commissioned by the National Academies of Science for NSF Science of Science and Innovation Policy (SciSIP) program workshop, Washington, DC, September 2012.

Presentations

• Leahey, E. E. (2023, February).

  “Papers and Patents are Becoming Less Disruptive over Time”

  . Invited talk at the UIUC School of Information Colloquium series.
• Leahey, E. E. (2023, June).

  “Illuminating Dark Matter”

  . Invited Keynote at International Conference on Science of Science. Northwestern University, Evanstan, IL.
• Leahey, E. E. (2023, March).

  “What Types of Novelty are Most Disruptive?”

  . Invited talk @ MIT Sloan School of Management, Economic Sociology group. Cambridge, MA: MIT SLoan School.
• Leahey, E. E. (2023, May).

  “What Types of Novelty are Most Disruptive?”

  . Invited talk at Nordic Network for the Science of Science, Odense, Denmark. Odense, Denmark.
• Leahey, E. E. (2023, November).

   “Transfer and Translation at the University”

  . Invited presentation at University of the Future Symposium, University of Tubingen (Germany).
• Leahey, E. E. (2023, October).

  "Disruption in Science: Trends, Patterns, and Correlates"

  . Invited keynote at Leibniz Center for Science and Society & DZHW, Hanover, Germany.
• Leahey, E. E. (2023, September).

  "How Science Policy Shapes the Nature of Scientific Work” 

  . CWTS Speaker series at Leiden University. Leiden, NL: CWTS.
• Leahey, E. E., Nanoti, A., Langalia, M., Lee, J., Gomez, C. J., & Bratt, S. E. (2023, June). Division of Labor in Data-Intensive Science: Implications for Innovation and Equity. 2nd International Conference of Science of Science & Innovation (ICSSI). Kellogg Global HUB, Northwestern University, Evanston, IL, USA: Digital Science.
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  In this paper, we systematically analyze the international division of labor on 1.2 million datasets submitted to GenBank over 29 years (1992-2021). GenBank [1] is an international open research data repository for the genomics community hosted by NCBI – and through which the Human Genome Project was conducted and COVID-19 sequences submitted – mak- ing it an ideal site to analyze the global distribution of labor on datasets. To classify countries, we use the the World Bank Income Classification [2] and a newer measure, the Scientific and Technical Capacity Index (STCI) [7], nuancing the binary of N-S. We analyzed the yearly struc- tures and dynamics of the division of N-S division of labor on genomic datasets by calculating the ratio of overlap of scientists appearing as (co)contributors to the dataset and on the dataset’s associated publication(s), inferring that a higher overlap is indicative of “coreness” in flat teams [8]. Coreness is indicative that the dataset submitter is more ‘core’ to the project, indicating the technical labor on a project is drawn into the intellectual center of the study. We find: (1) Scientists from the global south tend to be listed as datasets contributors more often that of global north researchers. Overlap increases overall, but there remain dis- tinct functional roles; that is, 40 percent of scientists are only dataset contributors. This finding is surprising given prior studies reporting the lack of infrastructures to produce and curate data in low income or scientifically developing countries. However, it could be that contribution is explained by the high frequency of N-S collaborations in genomics research on infectious diseases [5], leading to southern scientists being equipped to collect and submit datasets. (2) We identify a positive relationship between the “flatness” of a team and southern scientists leading or last author on the publication.
• Leahey, E. E. (2021). What Types of Novelty are Most Disruptive. Academy of Management. zoom.
• Leahey, E. E. (2021). “What Types of Novelty are Most Disruptive?”. Invited talk at Brown UniversityDepartment of Sociology.
• Leahey, E. E. (2021, August). Historical Dynamics of Disruption in Science and Technology. Academy of Management. zoom.
• Leahey, E. E. (2021, August). “Universities’ Commitment to Interdisciplinary Research: Causes and Consequences.”. Invited talk at Network of Inter- and Trans-disciplinary Research Organisations (NITRO) – Oceana. Australia (via Zoom).
• Leahey, E. E. (2021, December). “What Types of Novelty are Most Disruptive?”. Invited talk at Leiden UniversityCWTS.
• Leahey, E. E. (2020, Fall). What Types of Novelty are Most Disruptive?. UNC Sociology Colloquium. Zoom: UNC Chapel Hill Sociology.
  More info

  I was asked to give the kick-off talk for UNC Sociology's 2020-21 lecture series.
• Leahey, E. E., & Lee, J. (2020, summer). What Type of Novelty are Most Disruptive?. Indiana University Network Science Institute, CADRE Project. Zoom.
  More info

  CADRE helped secure the data for this project and asked us to give a talk about our research.
• Leahey, E. E., & Lee, J. (2020, summer). What Types of Novelty are Most Disruptive?. Stanford Workshop on Computational Sociology. Zoom.
  More info

  Jina and I presented this paper and fielded questions while serving on a panel and Stanford's Computational Sociology Workshop in August 2020.
• Leahey, E. E. (2019, Spring). Keynote address: “The Impact of Interdisciplinarity on Scientists’ Careers”. Social Science Research Center, College for International Education Research International Conference (CIDER). Berlin, Germany (April). Berlin.
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  I was invited to give a talk summarizing a number of my works on interdisciplinarity.
• Leahey, E. E. (2019, fall). "The Contours of Interdisciplinarity". Uppsala University, Centre for Integrated Research on Culture and Society, workshop on “Why Interdisciplinarity?” Uppsala, Sweden. Uppsala University, Sweden.
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  I was invited to give a talk about my research program on interdisciplinarity.
• Leahey, E. E. (2018, August). “Studying Scientific Careers”. University of Arizona, Department of Planetary Sciences. UA campus.
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  I was asked to give a talk focused on my research about scientific careers.
• Leahey, E. E. (2018, January). “Infrastructure for Interdisciplinarity”. The National Academies of Science Innovation Policy Forum, “Workshop on Government Decision-Making to Allocate Scientific Resources”. Washington DC: NAS.
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  Invited talk.
• Leahey, E. E. (2018, May). Keynote Address: “Is Interdisciplinary Collaboration Worth the Trouble?”. Loma Linda University Health Collaboration Symposium. virtual: Loma Linda University.
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  Invited talk.
• Leahey, E. E., & Ring-Ramirez, M. (2018, October). “Universities’ Structural Commitment to Interdisciplinary Research”. University of Arizona, Computational Social Science Workshop. Tucson: CSS Certificate Program.
  More info

  Misty, a RA on my 2015-18 NSF project with Sondra Barringer, and I presented this paper at the bi-annual CSS workshop.
• Leahey, E. E. (2016, February). How Gender Informs Research Programs & Disciplinary Cultures. Is there a ‘gender-diversity dividend’ for science? Mapping the knowledge implications of increasing gender diversity in research.” NSF-sponsored workshop organized by Londa Schiebinger & Mathias W. NielsenStanford University.
• Leahey, E. E. (2016, February). Investigations in Interdisciplinarity. UA School of Information.
• Leahey, E. E. (2016, September). Is Interdisciplinary Collaboration Worth the Trouble?. German Center for Higher Education Research & Science Studies.
• Leahey, E. E., & Koppman, S. (2016, April). Risk and Reputation: How Professional Classification Signals Drive the Adoption of New Methods. Indiana University, School of Library and Information Science.
• Leahey, E. E. (2015, November). Prominent but Less Productive: The Impact of Interdisciplinarity on Scientists' Research. U Iowa colloquium.
• Leahey, E. E. (2015, fall). Prominent but Less Productive: The Impact of Interdisciplinarity on Scientists’ Careers. department colloquium. Iowa City, IA: Department of Sociology.
• Leahey, E. E. (2015, fall). Quantifying Science. workshop associated with the Conference on Complex Systems 2015. Tempe, AZ.
• Leahey, E. E., & McBee, D. (2015, AUgust). “New Directions in Interdisciplinary Training: Trials and Tribulations”. ASA annual meeting. Chicago, IL.
• Leahey, E. E., & McBee, D. (2015, fall). Trails and Tribulation of Interdisciplinary Research. 4S (Society for the Social Studies of Science) Annual Meeting. Denver, CO.
• Leahey, E. E. (2013, August). How Gender Informs Research Programs and Disciplinary Cultures. ASA annual meeting.
  More info

  I was invited to present a synopsis of three of my research papers at a thematic session at the annual ASA meeting.
• Leahey, E. E. (2013, May). The Impact of Interdisciplinarity on Scientists' Careers. Global Young Academy.
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  I was invited to present my research at the Global Young Academy meeting in Hannover, Germany.
• Leahey, E. E. (2013, May). The Impact of Interdisciplinarity on Scientists' Careers. University of Chicago Booth School of Business.
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  I was invited to present my research to the markets and Organizations group.
• Leahey, E. E. (2012, 2012-10-01). The Impact of Inter-disciplinarity on Scientists' Careers. Penn State Department of Sociology. Penn State University.
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  I was invited to give a talk at Penn State Department of Sociology.
• Leahey, E. E. (2012, August). Interdisciplinarity: Theory, Methods, and Data. Academy of Management. Boston, MA.
  More info

  This was a Professional Development Workshop I was asked to co-lead. It was my first time attending the Academy of Management meeting.
• Leahey, E. E., Beckman, C., & Stanko, T. (2012, 2012-08-01). The Impact of Inter-disciplinarity on Scientists' Careers.. ASA. Denver, CO.
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  Academic conference presentation: American Sociological Association

Poster Presentations

• Leahey, E. E., Lee, J., Langalia, M., Devitt, W., Gomez, C. J., & Bratt, S. E. (2023, June). North-South Collaborations on Scientific Datasets: A Longitudinal Exploration (1992-2021). 2nd International Conference of Science of Science & Innovation. Kellogg Global HUB, Northwestern University, Evanston, IL, USA: Digital Science.
  More info

  In this paper, we systematically analyze the frequency of N-S collaborations on approx- imately 1.2 million sequences submitted to GenBank over 29 years (1992-2021). GenBank [2] is an international open research data repository for the genomics community hosted by NCBI, and in which the Human Genome Project sequences were shared and infectious disease sequences submitted (including COVID-19) making GenBank an ideal site to analyze N-S col- laborations on datasets. To classify countries we use the World Bank Income Classification [4] and the Scientific and Technical Capacity Index (STCI) [11]. We find: (1) datasets are disproportionately produced by the global north, but there is a higher rate of collaborations between nations with discrepant S&T capacity on datasets over time. The preponderance of the datasets submitted are domestic collaborations, but where there is international collaborations, over 89 percent are collaborations among scientifically advanced countries. The N-S collaborations networks demonstrate “burstiness” in their forma- tion and dissolution [5], suggesting scientific reactivity to outbreaks of infectious disease (e.g. HIV/AIDs) and ad hoc influx of resources to build capacity in southern scientists’ institutions (see Figure 1). (2) The classification indices commonly used to characterize the global north and south at a national level are incompatible revealing a need for composite mea- sures to nuance the N-S binary. The S&T capacity index [11] to the need for measures that capture the multi-faceted nature of the N-S political economy [1, 7], where S&T capacity and income measures are not interchangeable. For instance, United Arab Emirates is classified as a High Income Country (HIC) by the World Bank income classification, but as a Scientifically Lagging Country (SLC) by the parameters of the S&T index.

Others

• Leahey, E. E., & Koppman, S. (2013, September). Disciplinary Trading Zones: A Focus on Methodological Imports..
  More info

  We began collecting data for this ConfluenCenter funded project.
• Leahey, E. E. (2017, December). Infrastructure for Interdisciplinarity. A Science Policy Report prepared for NSF and the National Academies, funded by NSF award #1723536.
• Leahey, E. E. (2016, July). The Perks and Perils of Interdisciplinary Research. Social Science Research Council’s online Items series. http://items.ssrc.org/the-perks-and-perils-of-interdisciplinary-research/
• Leahey, E. E. (2017, January). Interdisciplinary research may lead to increased visibility but also depresses scholarly productivity. LSE Impact Blog. 23 January 2017. http://blogs.lse.ac.uk/impactofsocialsciences/2017/01/19/
• Leahey, E. E. (2017, January). Prominent but Less Productive: The Impact of Interdisciplinarity on Scientists’ Research. The ASQ Blog. https://asqblog.com/2017/01/25/leahey-beckman-stanko-2016/