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Record W2035756158 · doi:10.1191/0309132504ph496oa

Convergence, the institutional turn and workplace regimes: the case of lean production

2004· article· en· W2035756158 on OpenAlexaboutno aff
Tod Rutherford

Bibliographic record

VenueProgress in Human Geography · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsCapitalismConvergence (economics)EconomicsProduction (economics)Lean manufacturingCapital (architecture)Economic systemPoliticsPolitical scienceEconomic growthMicroeconomicsLaw

Abstract

fetched live from OpenAlex

The principal focus in this paper is a sympathetic critique of the institutional turn in economic geography and its analysis of convergence in contemporary capitalism. While insightful, this perspective does not fully capture the dynamic and contradictions of capitalist development and has tended to neglect the role of labor-capital relations in how systems of work organization develop. Following Jessop (1999; 2001), I argue that macroeconomic competition driven by the law of value disrupts institutions and acts as a ‘disembedding’ force for convergence within capitalism. In the workplace these tendencies are mediated by labor's ability to resist capital through what Burawoy (1985) terms the production politics of workplace regimes. I then illustrate these general points via an analysis of lean production in the automobile industry. Lean production is associated with strong convergence tendencies, because TNC reorganization facilitates the increased comparability of work quality and intensity across space. However, drawing upon the research of Lewchuck et al. (2001) and others on lean production and workers in Canada, the UK and Germany, I argue that, while national regimes are declining relative to firm-specific ones, workplace regimes continue to be an active force for divergence.

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 score0.402
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.239
Teacher spread0.217 · 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

Citations11
Published2004
Admission routes1
Has abstractyes

Explore more

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