Nouvelles technologies = nouvelles qualifications? Le cas des caissières de supermarché
Bibliographic record
Abstract
Cet article porte sur les qualifications présentes dans un travail considéré comme non qualifié, celui des caissières de supermarché, au Brésil et au Québec. Les effets de l'introduction des nouvelles technologies sur les qualifications des travailleuses dans ces deux sociétés font aussi l'objet de nos préoccupations. Après avoir présenté brièvement le débat concernant les effets des nouvelles technologies sur les qualifications des travailleuses, nous présentons les qualifications des caissières dans les supermarchés non automatisés. Nous analysons ensuite l'introduction des nouvelles technologies dans les supermarchés et leurs effets sur les qualifications des caissières dans ces deux sociétés. Nous concluons que le coeur de leurs qualifications, c'est-à-dire les qualifications sociales, n'a pas été touché par l'introduction des nouvelles technologies.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 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".