Bibliographic record
Abstract
À l’automne 2007 au Lac-Saint-Jean, l’initiative d’un grand-père (Régis Tremblay) à l’endroit de ses deux petits-fils (Maxime et Alexis) a déclenché une véritable déferlante qui s’est répandue d’abord aux villages circonvoisins avant de déborder dans les autres régions du Québec, puis dans certaines provinces canadiennes à partir de son lieu d’origine : Lac-à-la-Croix−Métabetchouan. Il s’agit de la chasse aux lutins. De manière spontanée, Régis Tremblay s’est approprié une ancienne croyance et l’a réinventée pour satisfaire l’imaginaire des enfants, avides de merveilleux. Cet article se propose de remonter à la genèse de ce phénomène qui prend de l’ampleur afin d’en comprendre à la fois la contagion qu’il a engendrée auprès des enfants, contagion qui a fini par emporter l’adhésion de leurs parents, et les enjeux ludiques et sociaux impliqués par sa propagation.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".