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Record W7044296155

Worker power, rent-seeking and income inequality in Canada: A sector-level analysis

2022· preprint· en· W7044296155 on OpenAlexaboutno aff

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic inequalityIncome inequality metricsIncome distributionDistribution (mathematics)InequalityContext (archaeology)Bargaining powerPanel Study of Income DynamicsIncome shares
DOInot available

Abstract

fetched live from OpenAlex

Neoclassical economics' explanations of the income distribution typically ignore the role of various forms of power. This paper explores the relationships between worker power, market power, rentseeking and the income distribution using a novel panel dataset on sector-level income distributions in Canada from 2000-2019. Levels of within-sector inequality were relatively stable throughout this time period but there is significant between-sector variation. Finance and insurance contributes disproportionately to top-end income inequality. Workers' bargaining power explains a significant portion of between-sector variation in inequality. Increases in market power and decreases in unionization are related to increases in sector-level income inequality. Increases in real average incomes at the sector level are associated with increases in top shares three years later and this effect is mitigated by high unionization. Results are discussed within the broader context of Canadian income inequality and the relationship between power and wage-setting.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.010
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.265
Teacher spread0.235 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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