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Contrate quem luta: movimento dos trabalhadores sem-teto, tecnologias e economia digital solidária

2024· article· pt· W4404044804 on OpenAlexaff
Julice Salvagni, Rafael Grohmann, Victória Mendonça da Silva

Bibliographic record

VenueSociedade e Estado · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolitical scienceSociologySocial science

Abstract

fetched live from OpenAlex

Resumo Este artigo tem o objetivo de analisar elementos de organização da iniciativa Contrate Quem Luta, do Movimento dos Trabalhadores Sem-Teto (MTST), enquanto experiência de tecnologia e trabalho em contexto de economia digital solidária. A partir de entrevistas com trabalhadores do projeto, reflete-se sobre a organização do trabalho e a perspectiva da economia digital solidária; a práxis do movimento social; e a organização da política de base. O MTST se organiza a partir do território, que precede a construção de tecnologias, e da práxis, articulada à construção de conceitos como o de soberania digital popular. Diante disso, pode-se argumentar que o Contrate Quem Luta tem a vantagem do estofo institucional do movimento social para se estabelecer, o que possibilita um fortalecimento da luta e da organização. Os trabalhadores não são apenas prestadores de serviço, eles auxiliam, também, na circulação das palavras e das lutas dos sem-teto.

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)0.005
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0070.015
Scholarly communication0.0180.009
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.021
GPT teacher head0.281
Teacher spread0.259 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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