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Record W7098091855

Changing the Rules Midway: The Impact of Granting Alimony Rights on Existing and Newly-Formed Partnerships.” Unpublished manuscript

2011· article· en· W7098091855 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsAlimonyCohabitationLegislatureMatching (statistics)Affect (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

The paper analyzes the effect of a reform granting alimony rights to cohabiting couples in Canada, exploiting the fact that each province extended these rights in different years and required different cohabitation length. A theoretical analysis, based on a collective household model with a matching framework, predicts that changes in alimony laws would affect existing couples and couples-to-be differently. For existing couples, legislative changes aimed at favoring (wo)men do benefit them, especially if the match quality is low. However, for couples not yet formed, they generate offsetting intra-household transfers (in our model, of leisure) and lower intra-marital allocations for the spouses who are the intended beneficiary. Our empirical analysis confirms these predictions. Among cohabiting couples united long enough before the reform, obtaining the right to petition for alimony led women to lower their labor force participation. These results, however, do not hold — and, in some cases, are reversed — for newly formed cohabiting couples. Carolina Gonzalez-Velosa provided very useful research assistance. We acknowledge useful comments we received

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.001

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 head0.152
GPT teacher head0.323
Teacher spread0.171 · 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 designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

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