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Record W2104402936 · doi:10.1111/area.12052

Cooperative recycling in <scp>S</scp>ão <scp>P</scp>aulo, <scp>B</scp>razil: towards an emotional consideration of empowerment

2013· article· en· W2104402936 on OpenAlexaff
Neil Nunn, Jutta Gutberlet

Bibliographic record

VenueArea · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of VictoriaUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsEmpowermentContext (archaeology)Power (physics)Metropolitan areaSociologyHegemonySocial psychologySet (abstract data type)PsychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This study, set in the context of a group of recycling cooperatives in the greater metropolitan region of São Paulo, Brazil, is about the relationship between emotional geographies and notions of empowerment. Paying attention to the ways that emotional expressions of empowerment deconstruct and subvert oppressive relations of power, while simultaneously reproducing and obscuring these same oppressive hegemons, we ask: what emotions are collectively felt by those who ascribe to the movement? And more importantly, what do these collective emotions do? How do emotions align individuals with particular collective values, and how do these emotions work in relation to systems of domination? Due to the cooperatives' location within Brazilian hegemonic systems of social domination, we argue that viewing empowerment as an emotion ‘I feel empowered’ rather than something one is or one achieves ‘I am empowered’ offers the space to consider the necessarily paradoxical nature of empowerment.

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 score0.020
Threshold uncertainty score0.040

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 studies0.0100.008
Scholarly communication0.0020.002
Open science0.0000.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.325
Teacher spread0.287 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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