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Record W1598984332

Tax Incentives and Fertility in Canada: Permanent vs. Transitory Effects

2002· preprint· en· W1598984332 on OpenAlexaboutno aff
Daniel Parent, Ling Wang

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2002
Typepreprint
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveHumanitiesPolitical scienceFertilityGeographyDemographic economicsDemographyWelfare economicsEconomicsSociologyPopulationArt
DOInot available

Abstract

fetched live from OpenAlex

Cette étude cherche à déterminer si l'effet de court terme des incitatifs fiscaux sur la décision d'avoir des enfants est de nature transitoire (par lequel seul le moment choisi pour avoir des enfants change) ou permanents (par lequel la taille ultime de la famille change). En utilisant des différences interprovinciales dans la mise en ?uvre du programme fédéral canadien d'allocations familiales au milieu des années 70, nous sommes en mesure d'estimer un effet de court terme substantiel pour les familles du Québec, particulièrement dans le cas des familles ayant préalablement deux enfants ou plus. Toutefois, les données des recensements de 1981 et 1991 montrent que les mêmes cohortes de femmes au Québec qui ont réagi fortement à l'incitatif financier à court terme ont ensuite diminué leur taux de fécondité relativement aux femmes ailleurs au Canada. Ces résultats nous donnent à penser que l'impact du programme fut essentiellement transitoire. En somme, bien que le coût d'avoir des enfants ait son importance comme facteur influençant la décision d'en avoir, l'effet semble opérer sur le moment choisi et non sur le nombre.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.012
GPT teacher head0.220
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

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