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Record W4286438186 · doi:10.3138/cpp.2020-142

Cohort Size and Youth Earnings: Evidence from Ontario

2022· article· en· W4286438186 on OpenAlexaffvenueabout
Xian Zhang

Bibliographic record

VenueCanadian Public Policy · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsMcGill University
Fundersnot available
KeywordsEarningsCohortDemographic economicsShock (circulatory)BachelorWageLabour supplyCensusDemographyLabour economicsCohort effectEconomicsHourly wagePolitical scienceMedicineSociologyPopulationAccounting

Abstract

fetched live from OpenAlex

This article studies a policy change in Ontario that reduced the duration of high school from five to four years. A result of this educational reform was the creation of the Ontario double cohort: the last cohort educated in the old secondary school system and the first cohort educated in the new one. Although they started school at different times, both cohorts graduated from high school in 2003. Four years later, Ontario experienced a 28 percent increase in new university graduates. By comparing the pre- and post-reform wage gap between new entrants and seasoned workers with a bachelor’s degree in Ontario versus that in the rest of Canada, I identify the impact of an excess labour supply shock on earnings. A triple-difference estimation using Canadian Labour Force Survey data suggests that the labour supply shock decreased the hourly wage rate by 7.6 percent among recent university graduates, which corroborates the result obtained using Canadian Census data. I also find that the labour supply shock decreases the proportion of university graduates taking a full-time job in the first year of their career. Moreover, I observe an increase in the proportion of recent university graduates working in small firms and landing in a low-paid occupation and industry. Last, I find that the depressing effect on wages is long-lasting. The negative impact on the wage rate persists for at least ten years after graduating from university.

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)0.005
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 score0.014
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.214
Teacher spread0.178 · 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

Citations0
Published2022
Admission routes3
Has abstractyes

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