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Record W2547922384

Unions and Traditionally Disadvantaged Workers: Evidence from Union Wage Premiums in Canada 2000 to 2012

2016· article· en· W2547922384 on OpenAlexaboutno aff
Rafael Gómez, Danielle Lamb

Bibliographic record

VenueE-Journal of international and comparative labour studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantagedWageLabour economicsCollective bargainingEconomicsImmigrationEarningsTrade unionDisadvantageGlobalizationDemographic economicsPolitical scienceEconomic growthMarket economy
DOInot available

Abstract

fetched live from OpenAlex

It is well documented that unionised workers earn significantly more than their non-union counterparts. However, over the last three decades, the union wage premium along with overall union coverage has fallen in most industrialized economies. Though the principal causes are still under dispute, the effects of technological change, managerial opposition, globalization and other factors have clearly lessened the bargaining power of labour with respect to employers. Given the commensurate rise of non-standard work and inequality in most developed nations, this paper examines the extent to which unions can still provide some immunity against the pressures of these “new labour market realities”.  Using data from the Canadian Labour Force Survey for the years 2000 – 2012 inclusive, we estimate union wage premiums amongst historically disadvantaged groups: i.e., youth, women, low wage workers, immigrants, Aboriginals and workers in non-standard jobs.  The results suggest that across almost every dimension of vulnerability or disadvantage used in the paper, unions are associated with a larger than average positive impact on workers’ earnings. The findings support the powerful redistributive role that unions still play in contemporary economies especially for the most vulnerable

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.655
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.067
GPT teacher head0.346
Teacher spread0.280 · 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

Citations34
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueE-Journal of international and comparative labour studiesSame topicLabor Movements and UnionsFrench-language works237,207