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Mopping up the labour shortage: the privatisation of waste management and gendered work reorganisation

2008· article· en· W2332480932 on OpenAlexaff
Mélanie Samson

Bibliographic record

VenueWork Organisation Labour & Globalisation · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSouth African History and Culture
Canadian institutionsYork University
FundersAfrican Union
KeywordsEconomic shortageMasculinityWorkforceWork (physics)Division of labourProfit (economics)SociologyLabour economicsGender studiesEconomic growthPolitical scienceEconomicsEngineeringLaw

Abstract

fetched live from OpenAlex

This article explores the gendered nature of work reorganisation in Johannesburg's privatised Pikitup waste management utility. It establishes that feminist analysis requires an exploration of the historical production of gendered and racialised divisions of labour, the continuities and disjunctures that arise with privatisation, the consequences for men and women workers in the workplace and the home and the effects of men's gendered privileges. Because Pikitup's profit-generating strategy mapped onto a pre-existing gender division of labour, the all-male collection workforce was shielded from labour shortages that resulted in dramatic forms of work reorganisation in the feminised street cleaning sector. Male street cleaning workers experienced the same objective transformations in work organisation as their female counterparts. However, they were less compromised due to the power associated with their masculinity in both the workplace and the home, belying any notion of convergence of experience between male and female 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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.019
Scholarly communication0.0040.005
Open science0.0000.007
Research integrity0.0010.002
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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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 designQualitative
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
Published2008
Admission routes1
Has abstractyes

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