Investigating Open Access Publishing Practices of Early and <scp>Mid‐Career</scp> Researchers in Humanities and Social Sciences Disciplines
Bibliographic record
Abstract
Abstract Although open access (OA) to research outputs has been proven to improve research readership, citation, and impact, the uptake of OA in some disciplines has remained low. In this paper, we investigated and compared OA publishing practices of early career and mid‐career researchers in the Humanities, Arts, and Social Sciences (HASS) disciplines in Canada. The descriptive survey design with the use of online questionnaire was employed. Participants were drawn from a group of 15 public research universities via their openly available emails on university websites. Survey data was analyzed with descriptive and inferential statistics. Findings show that in the last three years, 74.1% of mid‐career researchers have published in OA journals, compared to 63.1% of early career researchers. However, OA publishing of monographs (21.3%) and conference proceedings (29.9%), as well as the frequency and extent OA publishing remains low among all participants. ANOVA results (F [2, 218] = 3.683, p = .027, 𝜂2 = .033) showed that 3.3% of the variance in researchers' OA publishing frequency can be attributed to their disciplines. Overall, OA publishing among researchers in the HASS disciplines is still low. Hence, there is a need to identify factors that facilitate or hinder HASS researchers' OA publishing.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchBibliometricsOpen science Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Scholarly communicationOpen science Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.021 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".