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Record W4385783944 · doi:10.1177/00104140231193017

Persecuted Minorities and Defensive Cooperation: Contributions to Public Goods by Hindus and Muslims in Delhi

2023· article· en· W4385783944 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComparative Political Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsQueen's University
FundersHarvard University
KeywordsPublic goodProsocial behaviorMainstreamSocial psychologyInequalityPolitical scienceAccountabilityNorm (philosophy)NormativeSociologyPsychologyEconomics

Abstract

fetched live from OpenAlex

How does intergroup inequality, specifically minority experiences of persecution, affect contributions to local public goods? Based on an original survey experiment and qualitative research in slums in Delhi, we examine how Hindus and Muslims respond to social norms around promoting cooperation on community sanitation. Mainstream theories of development predict greater willingness to contribute to public goods in more homogeneous areas. In contrast to the “diversity-deficit hypothesis,” however, we find that social accountability mechanisms are more effective among Muslims, a group that routinely faces discrimination and violence in India. We propose that this reflects “defensive cooperation,” or a set of coping strategies developed by minorities to navigate a hostile sociopolitical environment. Our findings point to a new mechanism that helps to enforce prosocial norms and, hence, public goods provision in multiethnic contexts.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.178
GPT teacher head0.461
Teacher spread0.283 · 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