Faculty at an R2 University Show Varied Perceptions Toward Publishing and Using Open Access Scholarship
Bibliographic record
Abstract
A Review of: Scott, R. E., Murphy, J. A., Thayer-Styes, C., Buckley, C. E., & Shelley, A. (2023). Exploring faculty perspectives on open access at a medium-sized, American doctoral university. Insights the UKSG Journal, 36(1), 1-14. https://doi.org/10.1629/uksg.620 Objective – To examine faculty members’ preferences, experiences, and current practices for publishing and using Open Access (OA) content. Design – Qualitative interviews and inductive coding of participants’ responses. Setting – Illinois State University (ISU), a public R2 university. Subjects – Twenty-five faculty members, representing all of ISU’s colleges. Methods – Authors recruited participants via a faculty electronic mailing list, selecting 25 faculty members representing all of ISU’s colleges, as well as differing academic ranks and length of time since earning their terminal degrees. Interviews were conducted, recorded, and transcribed over Zoom. Authors used inductive coding to identify themes, while also seeking input from participants and external professionals to guarantee accurate and detailed representation of participants’ responses to the interview questions. Main Results – All participants placed themselves somewhere on the spectrum between being completely opposed to, and enthusiastically participating in, OA publishing, with many noting tension between a principled belief in OA scholarship and difficulties with carrying out those beliefs due to journal quality or article processing fees. Some scholars were able to make use of grants, transformative agreements, or departmental funds to cover the costs associated with OA publishing. Disciplinary norms governed the sharing or use of unpublished, publicly accessible scholarship, with scholars in the sciences being more likely to place works in disciplinary repositories, such as arXiv. Participants expressed hesitation to post preprints to repositories due to lack of peer-review, legal considerations, and having one’s research ideas “scooped.” Lack of peer-review also contributed to hesitancy to cite preprints, although arXiv emerged as a highly regarded repository in terms of article quality for relevant scientific disciplines. Conclusion – The authors conclude that perceptions of OA publishing are heavily determined by disciplinary norms, leading to a broad range of practices even within an R2 university. This necessitates multiple approaches by libraries to make OA publishing more possible and palatable for scholars including facilitating access to funds that alleviate or cover article processing fees, hosting OA journals, and providing quality education and support for publishing in reputable OA journals in one’s field. The authors see sustained shifts toward publishing in OA models as also likely to lead to scholars' increasing their use of others’ OA materials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".