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Physical Capital and the Embodied Nature of Income Inequality: Gender Differences in the Effect of Body Size on Workers’ Incomes in Canada

2012· article· fr· W1512398433 on OpenAlexaffabout
Thomas Perks

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2012
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsEconomic inequalityWelfare economicsHumanitiesSociologyEconomicsDemographic economicsInequalityArtMathematics

Abstract

fetched live from OpenAlex

ABSTRACT Cette étude évalue les effets des dimensions du corps – mesurées en utilisant l'index de la masse corporelle – sur le maximum de revenus atteint par les travailleuses et travailleurs au Canada. En utilisant les données d'un échantillon national représentatif des Canadiens, des analyses factorielles montrent que le rapport entre la masse corporelle et le revenu est négatif dans le cas des travailleuses, tandis que dans le cas des travailleurs ce rapport est positif et non‐linéaire. L’étude est basée sur le concept de capital physique défini par Bourdieu et sur le développement de ce concept réalisé par Shilling. On y démontre que ces résultats représentent l'importance relative de la grandeur corporelle dans la production et perpétuation des inégalités des revenus au Canada. This study assesses the effects of body size—measured using the body mass index—on the income attainment of female and male workers in C anada. Using data from a national representative sample of C anadians, multivariate analyses show that, for female workers, the body size‐income relationship is negative. However, for male workers, the body size‐income relationship is positive and nonlinear. Using B ourdieu's conceptualization of physical capital, and Shilling's extension of it, it is argued that these results are suggestive of the relative importance of body size to the production and continuation of gender income inequality in C anada.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.028
GPT teacher head0.280
Teacher spread0.252 · 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.

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

Citations6
Published2012
Admission routes2
Has abstractyes

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Same venueCanadian Review of Sociology/Revue canadienne de sociologieSame topicSocial and Cultural DynamicsFrench-language works237,207