Impacts d'un choc commercial sur les occupations des travailleurs de l'industrie forestière canadienne
Bibliographic record
Abstract
Ce mémoire a pour objectif d'estimer l'impact d'un choc négatif de demande de travail sur les occupations des travailleurs de l'industrie forestière canadienne. Pour faire nos estimations, nous utilisons la méthode de différence en différences appliquée à un modèle de probabilités linéaires avec des effets fixes d'individu. Nous trouvons que la probabilité qu'un individu travaillant dans l'industrie forestière soit en emploi après 2007, donc de 2007 à 2010, est 4,1 points de pourcentage plus faible que pour les industries comparables. De plus, le taux de fréquentation scolaire est 0,5 point de pourcentage plus élevé pour les individus ayant travaillé dans les secteurs primaire et secondaire avant 2007, donc en 2005 et 2006. \n______________________________________________________________________________ \nMOTS-CLÉS DE L’AUTEUR : Occupations, travail, industrie forestière canadienne, effet de traitement, choc commercial.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".