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Record W2156107655 · doi:10.1177/0002764211407832

Relocation Threats and Actual Relocations in Canadian Manufacturing: The Role of Firm Capacity and Union Concessions

2011· article· en· W2156107655 on OpenAlexaffabout
Patrice Jalette

Bibliographic record

VenueAmerican Behavioral Scientist · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsRelocationBusinessWork (physics)Value (mathematics)Industrial organizationLabour economicsDemographic economicsEconomicsEngineeringComputer science

Abstract

fetched live from OpenAlex

The goal of this article is to compare the situations of various plants in which there were relocation threats, some of which materialized and some of which did not. It is based on data collected through a survey of local unions in the manufacturing sector in the province of Quebec in Canada. The results show that certain structural characteristics of the plant, such as producing standardized products and being downwardly integrated into the value chain, were associated with a greater probability of a relocation threat. Furthermore, union concessions were linked with a decrease in the likelihood of an actual relocation. There was a significant association between actual relocation and concessions on employment levels but not between relocation and concessions on wages and benefits. In these relocation decisions, there were clearly two logics at work: managerial capacity to relocate and industrial relations dynamics.

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)0.004
metaresearch head score (Gemma)0.023
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 score0.990
Threshold uncertainty score0.634

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.312
Teacher spread0.272 · 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

Citations10
Published2011
Admission routes2
Has abstractyes

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