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Record W1873269241 · doi:10.47678/cjhe.v27i2/3.183308

Intermediate Skill Development in British Columbia: Policy Options for a Post-Industrial Era

2017· article· en· W1873269241 on OpenAlexvenueaboutno aff
Paul Gallagher

Bibliographic record

VenueCanadian Journal of Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Presentation (obstetrics)Context (archaeology)Public policyPublic relationsAction (physics)Work (physics)Political sciencePrivate sectorEconomic growthBusinessPublic administrationSociologyEconomicsEngineering

Abstract

fetched live from OpenAlex

As British Columbia's economy is increasingly shaped by post-industrial circumstances, it becomes necessary for that province, like others in Canada, to ensure that it has an adequate supply of workers with "new economy" knowledge and skills. How best to prepare people for "inter- mediate" skill work, requiring less than a university degree but more than secondary schooling, is the focus of this paper. An explanation of the need for different skills is followed by an analysis of recent interme- diate skill development policy and practice in B.C. That analysis draws particular attention to the roles of public and private training providers and concludes that these roles have been more overlapping than comple- mentary. The paper concludes with the presentation of five policy choices for government and the higher education community to consider as they address new labour force needs in a context of funding con- straints and changing social policy priorities. The need to design and develop a much more sophisticated, policy-oriented information base on intermediate skill development is presented as a major recommendation for follow up action.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.729

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0090.003
Scholarly communication0.0080.002
Open science0.0030.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.044
GPT teacher head0.362
Teacher spread0.318 · 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 designNot applicable
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

Citations3
Published2017
Admission routes2
Has abstractyes

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