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Record W4384823020 · doi:10.1111/gwao.13045

‘Our faces change, but it's always the same story’: Crises of social reproduction among informal recyclers in Buenos Aires, Argentina

2023· article· en· W4384823020 on OpenAlexafffund
Kate Parizeau

Bibliographic record

VenueGender Work and Organization · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of CanadaInternational Development Research CentrePierre Elliott Trudeau Foundation
KeywordsReproductionWork (physics)Psychological interventionSocial reproductionInformal sectorSociologyCorporate governancePrecarityEconomic growthGender studiesBusinessEconomicsPsychologySocial scienceSocial capitalEngineering

Abstract

fetched live from OpenAlex

Abstract This paper investigates the gendered dynamics of informal recycling in Buenos Aires, Argentina at a moment of transition in the governance of this work. I argue that there is a strong gender binary apparent in this type of informal work, and that the public nature of informal recycling can exacerbate the gendered crisis of social reproduction experienced by many women recyclers through inviting interventions into their work. This research is based on an extensive survey of informal recyclers and a series of interviews conducted between 2007 and 2011. In Buenos Aires, women's informal recycling work has had a more collective, social, and domestic image as compared to masculine industrial versions of this work. On average, women had more geographically limited experiences of the city and earned less money than men. Women carrying out social reproduction in public spaces were positioned as both needing assistance and deserving of it. The entwining of work and social reproduction for many women informal workers requires that any interventions to improve their work take into account the particular challenges associated with publicly performing the double burden of labor that they bear.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.050
GPT teacher head0.250
Teacher spread0.200 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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