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Record W3003949251 · doi:10.15173/glj.v11i1.4166

Ten Years of the Global Labour Journal: Reflecting on the Rise of the New Global Labour Studies

2020· article· en· W3003949251 on OpenAlexaffvenue
Edward Webster, Robert O’Brien

Bibliographic record

VenueGlobal Labour Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGlobal SouthWork (physics)Power (physics)Child labourSociologyAction (physics)Political sciencePolitical economyEconomicsEconomic geography

Abstract

fetched live from OpenAlex

The article examines the origins of the Global Labour Journal (GLJ) and its goal of broadening labour studies. It shows how, over the past decade, the GLJ has recorded and analysed the forms of action and organisation that fall outside the traditional focus of labour studies. Through a range of careful case studies, the Journal has made an important contribution to the growing field of global labour studies. The two topics that have been the focus of most attention across all types of submissions have been: 1) precarious work and new forms of labour struggles; and 2) international trade unionism or transnational/global labour. The Journal has been successful in giving a platform to content from the Global South, but it is uneven and limited. Another major limitation is the failure to bridge the divide between the big questions raised in the Marx/Polanyi debates during the early phase of the Journal with the more concrete accounts of labour rediscovering its power on the periphery of labour movement. The article concludes by pointing towards possible options facing labour and the choices facing the GLJ. KEY WORDS: Global labour; global labour studies; precarious work; future of labour

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)0.043
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.009
Science and technology studies0.0140.035
Scholarly communication0.0450.038
Open science0.0020.014
Research integrity0.0120.020
Insufficient payload (model declined to judge)0.0060.001

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 head0.058
GPT teacher head0.374
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations9
Published2020
Admission routes2
Has abstractyes

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