Researchers’ Perceptions and Experiences with an Open Access Subvention Fund
Bibliographic record
Abstract
Objective – This study investigated researchers’ perceptions of open access publishing and the ways in which the university’s open access subvention fund could evolve to meet the campus community’s needs. Methods – In spring 2021, two librarians conducted an anonymous survey using a convenience sample to recruit participants. The survey was directly distributed to 113 University of Idaho (U of I) affiliates who had received funding from, or expressed interest in, the open access subvention fund during the previous three years (FY 2019 to FY 2021). Other U of I affiliates were also offered the opportunity to participate in the survey via a link shared in the U of I’s daily email newsletter as well across the U of I’s graduate student email list. The researchers received 42 usable survey responses. The survey included 26 closed and open-ended questions and analysis included cross-tabulations based on fund applicant status as well as respondent role. Of the 26 questions, 4 were modified from a colleague’s previous study with U of I faculty members (Gaines, 2015). Results – Survey responses showed that interest in and support for open access were common among respondents. Although a majority of respondents had published an open access journal article and would like to continue to publish open access in the future, only 17% agreed that they had departmental support to do so. Results also demonstrated that researchers were less willing to pay article processing charges (APCs) out-of-pocket and preferred for funding to come from grant budgets first, followed by Office of Research Budgets, department or college budgets, and library budgets. Respondents expressed support for many of the open access subvention fund’s current criteria and processes, but they also indicated an interest in establishing a more equitable fund distribution cycle and allowing researchers to seek pre-approval once their article was accepted for peer-review. Findings related to open access publishing perspectives built upon previous research conducted at the U of I (Gaines, 2015) and across other institutions. Conclusion – This study confirmed the importance of evaluating and assessing library programs and services to ensure that they continue to meet the needs of campus communities. Through the study results, the researchers demonstrated that respondents were interested in open access publishing and the continuation of the open access subvention fund, as well as offering the U of I an opportunity to adjust the open access subvention fund’s processes to better serve researchers. These results also highlighted the need for those involved in open access publishing support to investigate new open access advocacy and education efforts to ensure that researchers receive the philosophical and financial support they need to pursue different models of scholarly publishing.
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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 | 0.040 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".