Bibliographic record
Abstract
Le confinement lié à la COVID‑19 et les répercussions économiques qui en découlent ont engendré un stress financier important chez les familles au Canada. Entre février et avril 2020, environ 1,3 million de personnes au Canada étaient au chômage, dont environ 97 % avaient récemment été mis à pied sur une base temporaire, ce qui signifie qu’elles peuvent s’attendre à retrouver leur emploi lorsque les restrictions liées à la pandémie seront assouplies1. Des recherches ont démontré que l’insécurité financière peut considérablement limiter l’accès à la nourriture pour les familles à faible revenu en plus d’accentuer les inégalités socioéconomiques2. D’autres facteurs, comme la santé et l’incapacité, le niveau de soutien social et la disponibilité restreinte de certains produits alimentaires, contribuent également à l’insécurité alimentaire pendant la pandémie de COVID‑19.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".