Libraries, Scholars, and Publishers in Digital Journal and Monograph Publishing
Bibliographic record
Abstract
As the budget increases of the post-World War II era that favoured science and education were being rolled back in the 1970s, information and communicational technological (ICT) development began to be rolled out. Research libraries responded by developing data systems and expertise that led eventually to new services such as institutional repositories and journal hosting. Twenty years later, continued ICT development encouraged entrepreneurship in digital journal publishing among a variety of scholars in Canada and elsewhere. Globally, public and private sector funded digital projects emerged aimed at regime change in the circulation of research knowledge. These dramatic developments are noteworthy for themselves as well as in recognition of valuable library/researcher partnerships that leave content to scholars and administration to libraries. On the whole, these partnerships have not been extended to university press-based monograph publishing with the presses joining as a third partner. Instead calls for reorganization verge on subordinating university presses to institutional mandates that could well diminish freedom of inquiry. A three-way partnership among scholars, libraries and publishing professionals has much to recommend it. Such a partnership, cast as constructivist inquiry, or social science and humanities R&D, would encourage extensive public sector participation scholarly publishing and open a long-overdue dynamic into the social science and humanities research.
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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 | 0.023 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.023 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.078 | 0.032 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.018 |
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".