Regards croisés sur la transmission : actes du 2ème colloque annuel du département \nd'anthropologie à l'UdeM (CADA), 2019
Bibliographic record
Abstract
Bloc (1). La transmission au sens classique. Transmission et partage : la ligne de vie comme outil de collaboration en anthropologie / Marianne-Sarah Saulnier ; Matsuri et jeunesse : apprentissage de l’identité japonaise / Michael Châteauneuf ; La transmission du titre d’empereur au Japon au 21e siècle / Bernard Bernier ; Bloc (2). La transmission et le contemporain. Du concours au rituel, épluchage et transmission / Ingrid Hall ; La transmission de la langue d’héritage au sein d’églises chrétiennes fondées par des immigrants à Montréal : idéologies et socialisation linguistiques / Adèle Copain ; Produire une immersion sensorielle virtuelle : le défi des créateurs de jeux vidéo / Véronique Leclerc ; Bloc (3). La transmission et l'histoire des concepts. Le présent continu du narcissisme de masse : misères contemporaines de la transmission selon la psycho-sociologie de Christopher Lasch / Olivier Bélanger-Duchesneau ; Pour une histoire conceptuelle du « terrorisme » / Corentin Sire ; La recherche participative en contexte inuit : quelques réflexions autour des concepts de réciprocité, d’épistémologie relationnelle et de transfert des connaissances / Pascale Laneuville.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".