Bibliographic record
Abstract
La correspondance entre l’ethnologue-folkloriste Luc Lacourcière (1910-1989), fondateur des Archives de folklore (1944) et professeur à l’Université Laval de Québec et le médiéviste Benoît Lacroix, o.p. (1915-), professeur à l’Institut d’études médiévales de l’Université de Montréal et fondateur du Centre d’études des religions populaires (1967), est provoquée par la lecture du premier d’un article du second, qui évoque les survivances médiévales au Canada français. Deux grands créateurs, tous deux scientifiques reconnus internationalement, récipiendaires de multiples prix et titres honorifiques, dont la correspondance – de quelque deux cents lettres retrouvées – aux appels et signatures variées, aux multiples trouvailles heureuses, recèlent des constantes, la mention de leurs cogitations, occupations, projets et réalisations, ainsi qu’une aide mutuelle réclamée et toujours au rendez-vous. Pour la résumer, une belle et fructueuse amitié reflétée dans une savoureuse correspondance que celle de Luc Lacourcière et de Benoît Lacroix.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".