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Record W1596707191

Trade Unions, Vocational Education and Workplace Training: International Trends

2015· article· en· W1596707191 on OpenAlexaboutno aff
Russell D. Lansbury

Bibliographic record

VenueE-Journal of international and comparative labour studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsPrerogativeVocational educationGeneral partnershipGovernment (linguistics)Social PartnershipWork (physics)Social partnersInvestment (military)BusinessTraining (meteorology)Trade unionEconomic growthPublic relationsPolitical sciencePublic administrationEconomicsPoliticsMarket economyFinanceInternational tradeLaw
DOInot available

Abstract

fetched live from OpenAlex

Trade unions are struggling to find an appropriate role in the changing world of work and skills requirements.  In coordinated market economies (CMEs), where there is a strong tradition of social partnership, shared responsibilities for vocational education and workplace training (VET) have been taken by government, employers, unions and individuals. Yet even in Germany and the Nordic countries, which have a long history of social partnership, there is growing resistance by employers to meet the costs of VET, except where these coincide with their own priorities. In liberal market economies (LMEs), such as the UK and Canada, unions have generally failed to establish long-term partnerships with employers in relation to training, which is generally regarded as a managerial prerogative. Some governments in LMEs have recognized the need for greater investment in VET but have been reluctant to legislate to require employers to fund industry-wide programs of VET and skills development or to ensure that unions are given a legitimate role in these matters.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.141
GPT teacher head0.415
Teacher spread0.274 · 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 designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

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