Bibliographic record
Abstract
Canadians are understandably nervous about retaining their separate identity, culture, and history in the context of a rapidly globalizing world. Although on the global stage we can boast of many highly talented, highly paid, and successful musicians, film stars, entertainers, and cultural industry entrepreneurs, as well as well known and respected writers and academics, at home we remain in the shadow of the United States, facing the relentless drive for open borders and freer trade. The book and periodical publishing industry is no exception. For scholarly journals there are concerns revolving around state support and pure survival. In addition, for history journals there are also issues of national identity and the teaching of that history in our schools and universities. This panel on scholarly publishing comes at an opportune time. While my own experience as a co-editor of the Canadian Historical Review ended after a three-year term in 1997, I have also spent three years on the Board of the Conference of Historical Journals (1996–1999), an organization which represents mainly American but also a number of Canadian history journals. These experiences have reminded me that, while Canadians have to be diligent about our own history, culture, and identity, we nevertheless share some common, or at least similar, dilemmas with colleagues in the United States and elsewhere. These common themes are the focus of what follows.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.017 | 0.035 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
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".