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Record W1640440581 · doi:10.1111/anti.12099

British Jobs for British Workers? Negotiating Work, Nation, and Globalisation through the Lindsey Oil Refinery Disputes

2014· article· en· W1640440581 on OpenAlexaff
Anthony Ince, David Featherstone, Andrew Cumbers, Danny MacKinnon, Kendra Strauss

Bibliographic record

VenueAntipode · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsSimon Fraser University
FundersJoseph Rowntree Foundation
KeywordsGlobalizationAgency (philosophy)SolidaritySociologyWorkforcePolitical economySloganPoliticsPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

Abstract This paper explores the relationships between labour organising, globalisation and national identity through an engagement with the 2009 Lindsey Oil Refinery strikes. Some strikers adopted the controversial slogan ‘British Jobs for British Workers’ in response to employers' attempts to undercut existing wages and conditions with a new migrant workforce. This led to accusations of xenophobia. We make three inter‐related arguments. First, we contend that it is necessary to interrogate the spatialised power relations generated through particular forms of labour agency enacted in relation to globalising processes. Second, since these responses can be politically ambiguous, success in territorially based disputes does not always equate with broader (transnational) class agency. Third, relevant to the project of labour geography, we propose that labour scholars and activists be more attuned to the mundane ambiguities in labour agency, and the subsequent need to frame local action within a broader relational politics of global labour solidarity.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.020
Scholarly communication0.0110.004
Open science0.0010.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.022
GPT teacher head0.276
Teacher spread0.254 · 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

Citations57
Published2014
Admission routes1
Has abstractyes

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