The Role of the State towards the Grey Zone of Employment: Eyes on Canada and the United States
Bibliographic record
Abstract
Dans la plupart des pays, le travail précaire est en hausse et les formes atypiques de travail se multiplient. Ce que nous appelons la « zone grise » de l’emploi résulte tant des transformations du travail typique que du travail atypique. En mettant l’accent sur la réglementation, les politiques publiques et le rôle de l’État dans la création et la perception de la zone grise, notre contribution consiste à relever les agissements ou les défauts d’agissements du gouvernement et les conséquences induites sur la relation d’emploi typique. En examinant et en comparant les conditions dans nos deux pays, le Canada et les États-Unis, nous montrons que l’État joue un rôle paradoxal dans la croissance du travail atypique et du travail précaire. Pour appuyer notre analyse, nous avons développé une matrice pour saisir les efforts ou les inerties du gouvernement. Nous concluons qu’il y a sept façons de comprendre le rôle joué par le gouvernement à l’égard de la zone grise.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".