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Record W3017090433 · doi:10.1080/13636820.2020.1744692

Canada’s high rate of short-cycle tertiary education attainment: a reflection of the role of its community colleges in vocational education and training

2020· article· en· W3017090433 on OpenAlexaffabout
Michael L. Skolnik

Bibliographic record

VenueJournal of Vocational Education and Training · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsWorkforceVocational educationEducational attainmentHigher educationPolitical sciencePopulationEconomic growthTraining (meteorology)Medical educationSociologyPedagogyGeographyMedicineDemographyEconomics

Abstract

fetched live from OpenAlex

Canada ranks first by a substantial margin among OECD member countries in the proportion of the adult population whose highest level of educational attainment is the completion of a programme of short-cycle tertiary education. Short-cycle tertiary education (SCTE) refers to the types of programmes typically offered by community colleges and similar educational institutions, of at least two years duration, and predominantly vocationally oriented. This article argues that Canada’s outlier status in SCTE attainment is largely due to its heavy reliance on community colleges rather than secondary schools, industry-based VET, or universities of applied sciences for workforce preparation. The article provides some data on the relative extent of use of these different vehicles for workplace preparation in Canada and some other countries, and it explores some of the implications of Canada’s reliance on community colleges for vocational education and training. Although the focus the article is on Canada, it raises general questions about international differences in workforce preparation strategies.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.074
GPT teacher head0.391
Teacher spread0.317 · 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 teacher head, 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

Citations19
Published2020
Admission routes2
Has abstractyes

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