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Record W3042546427 · doi:10.1177/0020715220940009

Redefining norms, exploring new avenues: Negotiations of women informal workers in Delhi

2020· article· en· W3042546427 on OpenAlexvenueno aff
Sakshi Khurana

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
FundersIndian Council of Social Science Research
KeywordsOppressionCONTESTNegotiationSociologyEthnographyWork (physics)Gender studiesInequalityPolitical scienceSocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

The changing nature of production activities in developing countries has brought into focus the contribution of large numbers of women who get pulled into the labor force either by choice or by compulsion. Women in the latter category often find themselves engaged in informal employment, in work that is inconsistent and low-paid, carried out under suboptimal working conditions. Their ability to improve their conditions of work and life is constrained not just by capitalist structures and the organization of production relations, but also by social structures of norms and cultural practices. The analysis in this article, based on ethnographic research among women engaged in the garment and construction industries in Delhi provides insights into the strategies that some women workers, in the two sectors that also largely comprised women belonging two different religious communities, adopt to contest precarious working conditions and patriarchal norms, and transition into more autonomous positions. This article asks that given the constraints particular to the garment and construction sectors, why and how do some women resist against structures of gender oppression? How do the differences or similarities in the socio-cultural norms of the two communities constrain and at times, also enable women’s choices and actions? This article brings forth the factors that lead women to resist against structures of gender oppression, challenge inequalities inherent in the organization of work, and the new meanings that they may assign to their own negotiations and interpretations of norms.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.027
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0270.047
Scholarly communication0.0150.006
Open science0.0030.017
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.251
GPT teacher head0.458
Teacher spread0.206 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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