Bibliographic record
Abstract
This paper reports on a qualitative study that aimed to discover faculty and graduate students’ reaction to journal cancellation projects. In most studies that examine cancellation projects the main aim is to delineate methods used in making decisions about cancellations and the process followed to achieve a successful outcome. Our study looked at these factors but also interviewed faculty to get their response to the cancellations that had occurred at their university and to discover whether there was an alignment between the different ways in which librarians and faculty evaluated journals. We interviewed fourteen librarians and thirteen faculty/graduate students from five medium-sized Canadian universities. Our analysis of the librarian interviews indicated that one of their major concerns when embarking on a cancellation project was the negative reaction they might get from faculty. To counteract this response, librarians made a concerted effort to make them aware of the upcoming cancellations and to provide alternative methods to access journals if their important journals were cut. From the faculty interviews we learned their reactions to these efforts and their knowledge of the journal publishing ecosystem. We also had librarians rank the importance of nine factors used when deciding to buy back journals, and asked faculty to indicate the importance of similar factors in their evaluation of journals. An interesting finding was that although librarians felt that citation metrics were the most important criteria to faculty in evaluating journals, faculty did not consider them as important as other factors. In conclusion we found that there was a stronger alignment between librarians’ and faculty/graduate students’ journal value metrics than librarians previously expected providing opportunities for them to work with faculty to find solutions to the current inequitable journal pricing situation.
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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 | 0.026 | 0.175 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".