An official website of the United States government
Abstract BackgroundSTEM minority participation programs have been widely implemented in higher education with the goal of diversifying the global STEM workforce. Informed by research highlighting the potential of targeted exploration of STEM roles and reflection on theselfin relation to STEM (identity exploration), this work examines how engagement in a government funded STEM minority participation program shaped these processes in current students and program alumni. ResultsEpistemic network analysis (ENA) was used to visualize conceptual connections between identity themes that emerged from interviews with present and past program participants. Network models were developed for current students and alumni for cross-group comparisons. Differences were found in how participants at different stages of their careers enact and describe their identity exploration processes. Summative network models highlighted how students discussed action-taking (sometimes through participation in STEM minority program initiatives) as they explored less-certain possible future STEM roles, while alumni integrated more diverse and holistic facets of their identities when conceptualizing their futures. To close the interpretive loop, a qualitative interpretation of interview discourse was used to give context to network patterns. ConclusionsResults highlight the differences between novices’ and professionals’ conceptualizations of their future selves and illustrate how minoritized individuals describe their long-term patterns of identity exploration related to STEM majors and careers. Implications for future STEM identity research and practice, including higher education programming as a tool to support students’ STEM identity exploration processes, are discussed.
more »
« less
Authors of misfortune: interpretation and expertise in a model disaster
Abstract Since 2001, beetles have killed two‐thirds of the pine trees in British Columbia, Canada, decimating the predominant commercial tree species in one of the world's largest timber economies. Attempts to construct and circulate computer models of the infestation and its aftermaths, however, have obscured destabilizing changes across state institutions for environmental research. Juxtaposing literary conceptualizations of distributed authorship with ethnographic critiques of technoscientific bureaucracy, this article examines how the proliferation of computer models in contemporary resource planning institutions has altered the ways experts participate in and sanction interpretive communities. The dynamic conceptualizations of authorship produced through these exchanges challenge existing portraits of anticipatory governance, an emergent mode of administration that often relies on models for procedural implementation and narrative framing even as it circumscribes modellers’ voices to specific moments of interpretation and critique. While modellers make claims on distant futures to provoke discussion among diverse actors, later interpreters may highlight a model's apparent precision or its radical uncertainties to defer criticisms of problematic interventions and government restructuring. Such modes of attribution have deepened many scientists’ sense of estrangement from the interpretive communities their models help to engender.
more »
« less
- Award ID(s):
- 2042012
- PAR ID:
- 10468795
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of the Royal Anthropological Institute
- Volume:
- 30
- Issue:
- 1
- ISSN:
- 1359-0987
- Format(s):
- Medium: X Size: p. 75-96
- Size(s):
- p. 75-96
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Education entails conflicting perspectives about its subject matter. In the late 1980s, the conflict developed into a war between interpretive and causal paradigms. Did the confrontation result in a balance between these warring sides? We use text analysis to identify research trends in 137,024 dissertation abstracts from 1980 to 2010 and relate these to students’ academic employment outcomes. Topics associated with the interpretive approach rose in popularity, while the outcomes-oriented paradigm declined. Academic employment remained stably associated with topics in the interpretive approach, but their effect is moderated by the prestige of the students’ institutions. The relation between topic popularity and employability provides insight into field change and how the benefits of cultural shifts fall along the lines of institutional power.more » « less
-
Abstract The recent development and use of generative AI (GenAI) has signaled a significant shift in research activities such as brainstorming, proposal writing, dissemination, and even reviewing. This has raised questions about how to balance the seemingly productive uses of GenAI with ethical concerns such as authorship and copyright issues, use of biased training data, lack of transparency, and impact on user privacy. To address these concerns, many Higher Education Institutions (HEIs) have released institutional guidance for researchers. To better understand the guidance that is being provided we report findings from a thematic analysis of guidelines from thirty HEIs in the United States that are classified as R1 or “very high research activity.” We found that guidance provided to researchers: (1) asks them to refer to external sources of information such as funding agencies and publishers to keep updated and use institutional resources for training and education; (2) asks them to understand and learn about specific GenAI attributes that shape research such as predictive modeling, knowledge cutoff date, data provenance, and model limitations, and educate themselves about ethical concerns such as authorship, attribution, privacy, and intellectual property issues; and (3) includes instructions on how to acknowledge sources and disclose the use of GenAI, how to communicate effectively about their GenAI use, and alerts researchers to long term implications such as over reliance on GenAI, legal consequences, and risks to their institutions from GenAI use. Overall, guidance places the onus of compliance on individual researchers making them accountable for any lapses, thereby increasing their responsibility.more » « less
-
Abstract The value of large‐scale collaborations for solving complex problems is widely recognized, but many barriers hinder meaningful authorship for all on the resulting multi‐author publications. Because many professional benefits arise from authorship, much of the literature on this topic has focused on cheating, conflict and effort documentation. However, approaches specifically recognizing and creatively overcoming barriers to meaningful authorship have received little attention.We have developed an inclusive authorship approach arising from 15 years of experience coordinating the publication of over 100 papers arising from a long‐term, international collaboration of hundreds of scientists.This method of sharing a paper initially as a storyboard with clear expectations, assignments and deadlines fosters communication and creates unambiguous opportunities for all authors to contribute intellectually. By documenting contributions through this multi‐step process, this approach ensures meaningful engagement by each author listed on a publication.The perception that co‐authors on large authorship publications have not meaningfully contributed underlies widespread institutional bias against multi‐authored papers, disincentivizing large collaborations despite their widely recognized value for advancing knowledge. Our approach identifies and overcomes key barriers to meaningful contributions, protecting the value of authorship even on massively multi‐authored publications.more » « less
-
Public organizations, including institutions in the U.S. criminal justice (CJ) system, have been rapidly releasing information pertaining to COVID-19. Even CJ institutions typically reticent to share information, like private prisons, have released vital COVID-19 information. The boon of available pandemic-related data, however, is not without problems. Unclear conceptualizations, stakeholders’ influence on data collection and release, and a lack of experience creating public dashboards on health data are just a few of the issues plaguing CJ institutions surrounding releasing COVID-19 data. In this article, we detail issues that institutions in each arm of the CJ system face when releasing pandemic-related data. We conclude with a set of recommendations for researchers seeking to use the abundance of publicly available data on the effects of the pandemic.more » « less
