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Record W3043335329

Private and Public Sector Bargaining in Canada: 1980-2015

2019· article· en· W3043335329 on OpenAlexaboutno aff
Joseph B. Rose

Bibliographic record

VenueInternational journal of employment studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsCollective bargainingBargaining powerPrivate sectorEconomicsPublic sectorPoliticsUnion densityLegislatureWageDuration (music)Project commissioningSettlement (finance)Labour economicsPublishingPolitical scienceEconomyEconomic growthLawFinanceMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Since 1980 collective bargaining has been influenced by significant economic, technological, political and legislative developments. This study compares the impact of these developments on selected collective bargaining indicators in the private and public sectors, including: union membership and density, the duration of collective agreements, settlement stages, wage settlements and strike activity. A key issue is to assess the overall impact of environmental pressures on collective bargaining trends and compare bargaining patterns between sectors. The study is based on unionization figures compiled by Statistics Canada and a special tabulation on other bargaining indicators provided by the Workplace Information and Research Division, Employment and Social Development Canada. Except for unionization, most bargaining indicators trended in the same general direction. However, there were notable differences in the magnitude and timing of these trends, and the underlying factors contributing to them. The findings reflect the erosion of the relative bargaining power of unions.

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 score0.159
Threshold uncertainty score0.975

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.013
Science and technology studies0.0060.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.340
Teacher spread0.292 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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