Bibliographic record
Abstract
Abstract. Poverty (low income) dynamics are explored using tax filer data covering the period 1992 to 1996. The distributions of short‐ and long‐term episodes are identified and reveal substantial differences by sex and family type. Entry and exit models explore the relationships between poverty transitions and sex, family status and other personal and situational attributes. Duration effects on exiting and re‐entering poverty are found to be important, and models including past poverty experiences point to strong ‘occurrence dependence’ for poverty entry and incidence. Fixed‐effect panel data models confirm the above and reveal asymmetries in the impacts of household transitions on poverty. JEL Classification: I3 La dynamique de la pauvreté : résultats empiriques pour le Canada. Les auteurs examinent la dynamique de la pauvreté(bas revenus)à l’aide des données disponibles pour les citoyens qui ont soumis leurs rapports d’impôt entre 1992 et 1996. On identifie les distributions d’épisodes (courts et longs) de pauvreté, et celles‐ci révèlent des différences significatives selon le sexe et les attributs familiaux. Les modèles d’entrée et sortie identifient les relations entre le statut de pauvreté, le sexe, le statut familial, et d’autres attributs personnels et situationnels. Il appert que les effets de durée sur les périodes de sortie et de ré‐entrée dans un statut de pauvreté sont importants; les modèles qui prennent en compte les épisodes de pauvreté antérieurs montrent qu’il y a une forte corrélation (occurrence dependence) tant pour le passage au statut de pauvreté que pour l’incidence de tels épisodes. Les résultats des études transversales confirment ces résultats et révèlent des asymétries dans les impacts des transitions dans les ménages sur la pauvreté.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.021 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".