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Record W1560504984

An Econometric Analysis of Intergenerational Reliance on Social Assistance

2000· article· en· W1560504984 on OpenAlexaff
Jean‐Yves Duclos, Bernard Fortin, Manon Rouleau

Bibliographic record

VenueCahiers de recherche · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsReceiptSocial assistancePsychologyEconometric analysisDemographyDemographic economicsDevelopmental psychologySociologyEconomicsEconomic growthEconometrics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the intergenerational transmission of participation in Qus social assistance program. The analysis takes into account two sources of intergenera- tional transmission. The first one is due to a correlation across generations of individual characteristics which influence participation. The second one is due to a causal link bet- ween parents' and children' s participation. We also attempt to identify the periods during which parental receipt of social assistance has the strongest influence on the child' s pro- pensity to replicate this behaviour during adulthood. Our data is from the administrative records of Qu´ ebec's Ministe de la Solidarit´ e Sociale and covers 17 204 young people who were 18 years old in 1990 and whose parents were recipients of social assistance du- ring at least one month between 1983 and 1995. Our results reveal that a ten-percentage point increase in the parental participation rate during the youth's pre-adult years (age 7-17) raises the youth's participation rate by about two percentage points during early adulthood (age 18-21). We cannot, however, statistically reject the hypothesis that the impact of parental participation on the child' s future participation rate is independent of the childhood period at which it is experienced.

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)0.016
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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.337
GPT teacher head0.482
Teacher spread0.145 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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