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Record W4292636447 · doi:10.3138/cpp.2020-098

The Effect of Quebec’s CEGEPs on Total Years of Schooling

2022· article· en· W4292636447 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Public Policy · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSpatial and Panel Data Analysis
Canadian institutionsGroup for Research in Decision AnalysisUniversité du Québec à Montréal
Fundersnot available
KeywordsMicrodata (statistics)CensusDemographyDemographic economicsGeographyFrenchPolitical scienceSocioeconomicsEconomic growthSociologyEconomicsPopulationArchaeology

Abstract

fetched live from OpenAlex

We describe the CEGEP ( collèges d’enseignement général et professionnel) innovation of the late 1960s in Quebec and study its early effect on total years of schooling in the province, with Ontario as control. We first compare the broad trends in post-secondary enrolment and credentials in Quebec and Ontario over the long period of 1960–2018. We then estimate the effect of the CEGEP reform on total years of schooling of the cohorts that were initially treated. To this end, we apply a simple difference-in-differences methodology to 2001 Census microdata for Francophone and Anglophone men and women. We find that the effect of CEGEPs has been broadly positive and significant.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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