Bibliographic record
Abstract
The argument is that Canadian and American historians need significant knowledge of European or Asian history if they are really to understand their own special subject—for at least three reasons. Without a significantly different subject to serve for comparison and contrast, the understanding of any given subject is impossible. The vast majority of our citizens/residents or their ancestors contributed a great part of their cultural heritage to our society. And 300 to 500 years is too chronologically shallow for anyone to grasp adequately the historical process. To illustrate the usefulness of such collateral knowledge, the experiences of four distinct European regions—the middle Danube, the Netherlands, the British Isles, and the Delian League of Ancient Greece—are briefly traced, with North American "applications" sometimes stated and sometimes left to be discerned. The concluding arguments stress the uniqueness of history in emphasizing TIME (the chronological environment) and the need to think metaphorically for understanding and communicating one's subject (the metaphors come from significantly different historical experiences, as well as from the arts).
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.024 | 0.016 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".