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Record W2048249061 · doi:10.1177/0160449x0002500304

Training and Equity Initiatives on the British Columbia Vancouver Island Highway Project: A Model For Large-Scale Construction Projects

2000· article· en· W2048249061 on OpenAlexaffabout
Marjorie Griffin Cohen, Kate Braid

Bibliographic record

VenueLabor Studies Journal · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsSimon Fraser UniversityVancouver Island University
Fundersnot available
KeywordsWorkforceEquity (law)BusinessEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The equity initiatives in training and hiring on this large project were unique and stunningly successful. At peak production periods the equity hires constituted more than 20 percent of the workforce, a figure that is ten times higher than normal. This project was the first time a significant effort had been made to integrate women and First Nations in a commercial highway project. It was accomplished through two risk- taking and innovative measures. One was a priority for equity hires in the collective agreement and the other was the establishment of a training site where women and First Nations (mostly male) built a section of the highway as part of the training process. This article examines these fea tures and the experiences of the workers, contractors, and trade unions with the equity initiatives. It pays particular attention to the construction industry workplace culture and how this affects training for equity groups.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.681

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.068
GPT teacher head0.346
Teacher spread0.278 · 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 designQualitative
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

Citations9
Published2000
Admission routes2
Has abstractyes

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