Bibliographic record
Abstract
Simon Laflamme examine la notion d’identité telle qu’elle se révèle dans les travaux des spécialistes des sciences humaines qui se sont penchés sur l’Ontario français. Après avoir mis en évidence des théories générales, somme toute récentes, dont les conclusions sont souvent mobilisées par les observateurs de l’identité dans un contexte franco-ontarien, puis planté quelques balises historiques, il considère les travaux selon leur domaine d’analyse : l’éducation, la politique et le juridique, le genre, la famille, les médias, les arts et les sports. Au terme de cette recension, il met en lumière les deux thèses qui polarisent le discours : l’une qui parle d’assimilation, soutenue entre autres par Roger Bernard, l’autre d’hybridité, avancée notamment par Christine Dallaire. Mais, entre ces perspectives, tout n’est pas qu’opposition, et l’auteur constate sans peine que les spécialistes de l’Ontario français oscillent entre elles deux, dès lors qu’ils ne perdent pas de vue les facteurs généraux en dehors desquels il n’y a pas d’identité.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.028 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".