MétaCan
Menu
Back to cohort
Record W2616511777 · doi:10.1086/703255

Push and Pull: Disability Insurance, Regional Labor Markets, and Benefit Generosity in Canada and the United States

2019· article· en· W2616511777 on OpenAlex
Kevin Milligan, Tammy Schirle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Labor Economics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsWilfrid Laurier UniversityUniversity of British Columbia
Fundersnot available
KeywordsGenerosityDisability insuranceLabour economicsEconomicsDemographic economicsHealth insuranceDisability benefitsInstrumental variableEconomic growthSocial securityPolitical scienceHealth careMarket economy

Abstract

fetched live from OpenAlex

Disability insurance take-up has expanded substantially in the past 20 years in the United States while shrinking in Canada. We empirically assess these trends by measuring the strength of the “push” from weak labor markets versus the “pull” of more generous benefits. Using an instrumental variables strategy comparing benefit changes across country, age, and year, we find that both benefits and regional wages matter. Simulations suggest that the upswing in disability insurance take-up in the United States would be reversed, dropping the caseload by 41% if benefits and wages had followed the growth path observed in Canada.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.281
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.292
Teacher spread0.248 · 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