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Record W3121435000

Union Raiding and Organizing in Ontario

2005· article· en· W3121435000 on OpenAlexaffabout
Timothy J. Bartkiw, Felice Martinello

Bibliographic record

VenueSSRN Electronic Journal · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsBrock UniversityToronto Metropolitan University
Fundersnot available
KeywordsCertificationLegislatureUnion densityGeographyDemographic economicsPolitical scienceEconomicsCollective bargainingArchaeologyLabour economicsLaw
DOInot available

Abstract

fetched live from OpenAlex

This paper provides the first analysis of aggregate raiding activity in Ontario by isolating raid applications from available certification data. Raiding in Ontario generally decreased over the 1975 to 2003 period save for the huge increases in 2000 and 2001 involving the CAW and SEIU. Bargaining units are significantly larger in raids, and legislative changes had little effect on aggregate raiding levels. Over most of the period raiding activity has been quite modest. Thus analyses of union organizing and its effect on union density are unlikely to be affected by leaving raids in the organizing data. An important exception occurs in 2000 and 2001, where the certification data seriously overstate new organizing. Corrected measures show that new (non-raid) union organizing continues to decline in Ontario. The decline in new organizing has been greater than the decline in raiding, resulting in an increased proportion of organizing due to raids in recent years.

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)0.003
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 score0.039
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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

Citations0
Published2005
Admission routes2
Has abstractyes

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