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Record W2991373194 · doi:10.1080/00346764.2019.1690671

Work autonomy and workplace democracy: the polarization of the goods of work autonomy in the two worlds of work

2019· article· en· W2991373194 on OpenAlexaff
Chi Kwok

Bibliographic record

VenueReview of Social Economy · 2019
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAutonomyDemocracyFraming (construction)PoliticsSociologyPolarization (electrochemistry)HarmDistributive justiceLaw and economicsEconomicsPolitical scienceEconomic JusticeLaw

Abstract

fetched live from OpenAlex

Political theorists have been framing the problems of unfreedom and domination at work as inconsistent with the requirements of political democracy, undermining the democratic potential of the workplace and inducing psychological and status harm. Although these are important insights, political theorists are often unwilling to frame the hierarchical workplace as an issue of distributive justice. This paper, by bringing in the empirical literature on work autonomy, offers a framework to explicate the relationship between freedom at work and the distribution of essential goods at paid work. Through such framework, the paper argues that procedural and substantive freedom at work are essential to the fair distribution of the goods of work. By examining the empirical literature, the paper further argues that there exists a polarization of the goods of work between high-skilled and low-skilled labor, and the polarization offers a pro-tanto justification of workplace democracy for the least advantaged workers.

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)0.004
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0020.023
Scholarly communication0.0080.007
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.356
Teacher spread0.332 · 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
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

Citations13
Published2019
Admission routes1
Has abstractyes

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