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Record W1542707703 · doi:10.1177/001979390706000401

Unions, Work Practices, and Wages under Different Institutional Environments: The Case of Canada and England

2007· article· en· W1542707703 on OpenAlexaffabout
John Godard

Bibliographic record

VenueIndustrial and Labor Relations Review · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsWageWork (physics)Representation (politics)Labour economicsCollective bargainingQuality (philosophy)EconomicsDemographic economicsBusinessPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Using data collected in 2003–2004 in national telephone surveys of 750 Canadian and 450 English workers, the author finds that alternative work practices (AWPs), such as autonomous teams, quality circles, and information sharing, provided meaningful pay gains for non-union workers but not union workers in both Canada and England. In Canada, non-union AWP payoffs approached union wage premia at even moderate levels of AWP adoption, suggesting that AWPs may serve as an alternative means to higher pay, one that is incompatible with unions and that could erode demand for union representation. In England, there was no meaningful union wage premium, suggesting that AWPs may have replaced pay bargaining as a means to higher pay; but an interaction term combining union representation and “best” HR practices bore a strong association with higher pay, consistent with a new economic role whereby unions achieve gains for their members through collaborative, performance-enhancing strategies.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.011
Science and technology studies0.0070.002
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.300
Teacher spread0.257 · 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 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

Citations18
Published2007
Admission routes2
Has abstractyes

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