Bibliographic record
Abstract
Identity – national, regional, gender, class, and ethnic – has dominated much of Canadian historical writing over the past century. In recent decades, the ‘limited identities’ hypothesis has played a major role in the flowering of social history whose dominance is now being called into question by proponents of a renewed ‘national’ approach. In this debate, one fundamental issue is being largely ignored: the easy assumption that identities, limited or national, are essential rather than contingent. Moreover, it is too often forgotten that identities are multiple rather than single. As always, in historical studies, the context is crucial. Abstract: Ľidentite – nationale, regionale, sexuelle, sociale et ethnique – a ete un theme dominant dans la plupart de ce qu’on a ecrit sur ľhistoire canadienne durant le siecle dernier. Au cours des dernieres decennies, ľhypothese de ľ « identite limitee » a joue un role majeur dans ľepanouissement de ľhistoire sociale dont la predominance est actuellement remise en question par les adeptes ďune nouvelle approche « nationale ». Il y a cependant au coeur du debat une question fondamentale qui reste en grande partie ignoree: c’est la simple supposition que ľidentite, qu’elle soit limitee ou nationale, est essentielle plutot qu’accidentelle. On oublie en outre trop frequemment que ľidentite a plus souvent de multiples facettes qu’une seule. Comme c’est toujours le cas dans les etudes historiques, le contexte est un element crucial.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.046 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".