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Record W2924757012 · doi:10.34989/san-2017-9

Labour Force Participation: A Comparison of the United States and Canada

2021· preprint· en· W2924757012 on OpenAlexaffabout
James Ketcheson, Natalia Kyui, Benoit Vincent

Bibliographic record

VenueRePEc: Research Papers in Economics · 2021
Typepreprint
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsBank of Canada
Fundersnot available
KeywordsPolitical scienceHumanitiesEconomicsArt

Abstract

fetched live from OpenAlex

This note explores the drivers behind the recent increase in the US participation rate in the labour market and assesses the likelihood of a similar gain in Canada. The growth in the US participation rate has largely been due to a pickup in the participation of prime-age workers following a post-recession decline. The prime-age participation rate in Canada, however, did not experience a significant drop following the 2008–09 recession, suggesting that the scope for drawing more prime-age workers into the Canadian labour force is more limited than in the United States. This does not preclude the possibility that the Canadian participation rate could rebound for other reasons, however. Indeed, the Canadian youth participation rate fell following the recession and could potentially recover in response to stronger labour market conditions. While the US youth participation rate also fell following the recession, this continued a long-standing trend decline in this rate, which suggests the recent drop in the United States could be more permanent.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.038
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.014
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.096
GPT teacher head0.442
Teacher spread0.347 · 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
Published2021
Admission routes2
Has abstractyes

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Same venueRePEc: Research Papers in Economics→Same topicEmployment and Welfare Studies→French-language works237,207→