Bibliographic record
Abstract
Cet article rend compte de l’émergence d’une pratique discrète de gestion des surplus alimentaires : le stockage et la redistribution depuis les frigos collectifs. Pour ce faire, il s’appuie sur une enquête ethnographique conduite entre 2016 et 2020 dans les villes de Montréal et de Québec. Il montre que ces pratiques s’insèrent dans les interstices du circuit classique de redistribution alimentaire pour proposer une gestion alternative des surplus. Les frigos n’opèrent toutefois pas en rupture avec le modèle des banques alimentaires mais plutôt en complémentarité, car ils offrent, à plus petite échelle, une avenue de plus pour disposer des surplus produits par l’industrie alimentaire. Aussi, c’est surtout dans le rapport aux donataires que les frigos apparaissent s’inscrire dans une pratique alternative. Avec le temps, ces frigos se révèlent néanmoins fragiles et tendent à disparaître ou à se formaliser.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".