Inequity, precarity, and disparity: Exploring systemic and institutional barriers in open access publishing
Bibliographic record
Abstract
Despite increasing advocacy for open access (OA), its uptake in some disciplines has remained low. Existing studies have linked the low uptake of OA in the humanities and social sciences (HSS) to disciplinary norms, limited funding for article processing charges (APCs), and researchers’ preferences. However, there is a growing concern about inequity in the scholarly communication landscape, as OA publishing has remained unaffordable to many researchers. This study investigates systemic and institutional barriers to OA publishing in Canada, as well as strategies for improving the uptake of and equity in OA publishing. Using semi-structured interviews, qualitative data was collected from 20 professors from the HSS disciplines of research-intensive universities in the country. Data was analyzed using the NVivo software, following the reflexive thematic analysis approach. Findings revealed five systemic and institutional barriers to OA publishing: (1) unaffordable APCs; (2) precarious career stage and tenure requirements; (3) unequal privileges; (4) gender; and (5) conflicting and unsupportive institutional OA policies. We conclude that there needs to be a concerted effort in promoting and funding viable and sustainable OA models, which removes the financial burden of OA publishing from researchers. There is also an increasing need to promote OA culture within academia and provide institutional support for OA publishing. Notably, the model of academic scholarship that places prominence on journal metrics for tenure and promotion needs to be reformed. Some recommendations for reducing systemic and institutional barriers to OA publishing are provided.
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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 | 0.047 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".