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Record W2103989343 · doi:10.7202/1008197ar

(Still) Up to No Good: Reconfiguring Worker Resistance and Misbehaviour in an Increasingly Unorganized World

2012· article· en· W2103989343 on OpenAlexaffvenue
Diane van den Broek, Tony Dundon

Bibliographic record

VenueRelations industrielles · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsResistance (ecology)Context (archaeology)Public relationsIndustrial relationsAssertivenessPolitical scienceBusinessSocial psychologySociologyPsychologyLaw

Abstract

fetched live from OpenAlex

The way worker resistance and misbehaviour have been analyzed has undergone significant transformation over the past few decades. While researchers have observed the quantitative decline of formal or organized forms of industrial relations conflict, others have highlighted the emergence of informal and individualized (mis)behaviours. There have been a range of reasons advanced to explain both the decline in industrial disputes and in the lineal approaches to analyze workplace conflict. This article cautions the increasing tendency to analyze resistance and misbehaviour in an institutional vacuum. Drawing on longitudinal research across multiple organizational settings in Australia and Britain, the article identifies the longevity of institutional and structural factors to explain workplace behaviours, particularly among weakly organized workers. The evidence presented in this paper emphasizes the need to analyze employee resistance within its institutional context. The range of behaviours identified here in many non- or anti-union settings were shaped by the changing structural and institutional workplace regime: by sector, size, structure or managerial strategy (among others). By recognizing the importance of context and place, we argue that what is often portrayed as types of misbehaviour substitute for more assertive forms of resistance by workers who are vulnerable in the labour market or denied access to traditional collective structures of representation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.987

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.291
Teacher spread0.261 · 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 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

Citations27
Published2012
Admission routes2
Has abstractyes

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