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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 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 score0.253
Threshold uncertainty score0.989

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 studies0.0010.000
Scholarly communication0.0010.000
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 head0.044
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 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

Citations3
Published2017
Admission routes2
Has abstractyes

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