Transmission intergenerationnelle du revenu : nouvelles donnees pour le Canada
Bibliographic record
Abstract
Dans le cadre des etudes comparatives de la mobilite intergenerationnelle des gains et du revenu, le Canada se classe generalement comme l'un des pays les plus mobiles parmi les economies avancees comme le Danemark, la Finlande et la Norvege. L'affirmation selon laquelle le Canada est une societe hautement mobile est fondee sur les estimations de l'elasticite intergenerationnelle du revenu dont font etat Corak et Heisz (1999). Corak et Heisz ont utilise les donnees d'une version anterieure de la base de donnees sur la mobilite intergenerationnelle du revenu (base de DMIR), qui fait le suivi du revenu des jeunes Canadiens uniquement jusqu'au debut de la trentaine. Des publications theoriques recentes proposent toutefois que la relation entre le revenu a vie des enfants et celui des parents ne peut pas etre estimee avec exactitude si l'on n?observe pas le revenu des enfants a la mi-carriere. C?est ce qu'on appelle le biais lie au cycle de vie. La presente etude se penche sur cette question en reexaminant l'importance de la mobilite intergenerationnelle des gains et du revenu au Canada a l'aide d'une version actualisee de la base de DMIR qui fait le suivi des enfants jusqu'à la mi-quarantaine avancee, ce qui permet d'observer le revenu a la mi-carriere
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 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".