Les transformations d'une chanson folklorique : du Moine Tremblant au Rapide-Blanc
Bibliographic record
Abstract
L’enquête ethnographique et folklorique a été 1' une des premières aussi bien que 1'une des plus consciencieuses et des plus systématiques manifestations de la recherche scientifique sur notre milieu. Les formes spontanées de la vie populaire traditionnelle : coutumes, dictons, légendes, contes, chansons, ont été l'objet de répertoires, d'inventaires, de monographies originales dont 1'ensemble constitue un trésor documentaire d'une richesse trop peu connue. L’initiative et le mérite de ces travaux reviennent en très grande partie, depuis vingt ans, à l'Institut de Folklore et aux Archives de Folklore de l'Université Laval et à leur directeur, M. Luc Lacourcière. Dans l'étude qui suit, M. Lacourcière récapitule les avatars' d’une chanson populaire qui a connu récemment une étonnante faveur publique. Sa patiente analyse folklorique décèle, par le recours à l'histoire et à la sémantique, la mystérieuse richesse des apports humains successifs dans 1' élaboration d'un phénomène social apparemment aussi banal qu’une simple chanson.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".