The Critical Role of Institutional Services in Open Access Advocacy
Bibliographic record
Abstract
This paper examines the development of the Open Access movement in scholarly communication, with particular attention to some of the rhetorical strategies and policy mechanisms used to promote it to scholars and scientists. Despite the majority of journal publishers’ acceptance of author self-archiving practices, and the minimal time commitment required by authors to successfully self-archive their work in disciplinary or institutional repositories, the majority of authors still by and large avoid participation. The paper reviews the strategies and arguments used for increasing author participation in open access, including the role of open access mandates. We recommend a service-oriented approach towards increasing participation in open access, rather than rhetoric that speculates on the benefits that open access will have on text/data mining innovation. In advocating for open access participation, we recommend focusing on its most universal and tangible purpose: increasing public open (gratis) access to the published results of publicly funded research. Researchers require strong institutional support to understand the copyright climate of open access self-archiving, user-friendly interfaces and useful metrics, such as repository usage statistics. We recommend that mandates and well-crafted and responsive author support services at universities will ultimately be required to ensure the growth of open access. We describe the mediated deposit service that was developed to support author self-archiving in Spectrum: Concordia University Research Repository. By comparing the number of deposits of non-thesis materials (e.g. articles and conference presentations) that were accomplished through the staff-mediated deposit service to the number of deposits that were author-initiated, we demonstrate the relative significance of this service to the growth of the repository.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.154 | 0.160 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.027 | 0.094 |
| Scholarly communication | 0.048 | 0.050 |
| Open science | 0.004 | 0.041 |
| Research integrity | 0.019 | 0.022 |
| Insufficient payload (model declined to judge) | 0.012 | 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".