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Record W2002956856 · doi:10.1111/irel.12072

Prevailing Wage Regulations and School Construction Costs: Cumulative Evidence from British Columbia

2014· article· en· W2002956856 on OpenAlexaboutno aff
Kevin Duncan, Peter Philips, Mark J. Prus

Bibliographic record

VenueIndustrial Relations A Journal of Economy and Society · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsWageLabour economicsEconomics

Abstract

fetched live from OpenAlex

The effect of prevailing wage laws on the cost of public construction has been the subject of an ongoing public policy debate. We measure this effect by comparing the public/private construction cost differential for schools built before and after British Columbia's Skills Development and Fair Wage Policy. Regression results indicate that public schools were 40.5 percent more expensive to build prior to the policy. This differential was 40.1 percent after the policy's enforcement. However, this change is not statistically significant. Regression results also indicate a stable construction cost function over the policy period. These results indicate that the effect of fair wage requirements was not different from zero in terms of magnitude or statistical significance. Combining these results with the findings of our previous research provides a comprehensive view regarding the effect of the British Columbian prevailing wage policy on school construction. This body of research, utilizing a variety of statistical methods, provides consistent evidence indicating that a relatively strong prevailing wage policy was not associated with changes in the efficiency or productivity of construction that contributes to increased building costs.

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 score0.569
Threshold uncertainty score0.626

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 communication0.0000.001
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 head0.048
GPT teacher head0.228
Teacher spread0.180 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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