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Record W6996431511

Rural region community cooperation, a Fast Track vocational technical education programme

2000· dissertation· en· W6996431511 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2000
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene Regulatory Network Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationEconomic shortagePosition (finance)Rural areaProduction (economics)Remedial educationTraining (meteorology)
DOInot available

Abstract

fetched live from OpenAlex

Shortages of skilled labour in Canadian industry require decisive nation wide action. If remedial action is not taken immediately, future ensuing reduced levels of production in Canadian manufacturing industries will restrict financial growth of Canada, and weaken the Canadian position in the global marketplace. Skill labour shortages in urban areas are exacerbated in rural areas and managers of rural industries are expressing concerns that with the shrinking size of the rural industrial skilled labour pool it is rapidly becoming increasingly difficult to run manufacturing operations. A case study method was chosen to describe the development and implementation of the 'Fast Track' vocational training programme, to evaluate the extent to which the stakeholders' expectations had been met, and to determine the perception of the programme held by the stakeholders. All graduates of the 'Fast Track' programme received offers of employment as industrial maintenance personnel by companies participating in the programme.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.430
Threshold uncertainty score0.855

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.003

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 head0.011
GPT teacher head0.231
Teacher spread0.219 · 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
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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