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Record W4311630748 · doi:10.1177/10659129221143763

Why the Public Supports the Human Rights of Prisoners and Asylum Seekers: An Experimental Approach

2022· article· en· W4311630748 on OpenAlexaboutno aff
Charles Crabtree, Jeong‐Woo Koo, Amanda Murdie, Kiyoteru Tsutsui

Bibliographic record

VenuePolitical Research Quarterly · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsPolitical sciencePublic opinionRhetoricInternational human rights lawRefugeeNorm (philosophy)Public policyLawLaw and economicsCriminologySociologyPolitics

Abstract

fetched live from OpenAlex

What factors shape support for the human rights of prisoners and asylum seekers at the individual level? Although the human rights literature has expanded greatly in the last 30 years, comparatively little attention has been paid to (a) the many human rights outside of a very small set of physical or bodily integrity rights and (b) the role of public opinion. We build a theoretical model of various human rights as public opinion-related policy choices, developing the micro-foundations of public support for the human rights of vulnerable subpopulations. Drawing on the broader literature on public policy and international norms, we use experimental methods to test whether calls to rational effectiveness or international norm cascades improve support for the rights of prisoners and asylum seekers. Although we find baseline support for these rights in the United States and Canada, our findings also imply that rhetoric on the potential costs of human rights policy could reduce popular support, even when such policy is consistent with international 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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.414
Teacher spread0.338 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2022
Admission routes1
Has abstractyes

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