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Record W2138795533 · doi:10.1002/ejsp.1990

Responding to historical injustices: Does group membership trump liberal‐conservative ideology?

2013· article· en· W2138795533 on OpenAlexafffund
Jillian C. Banfield, Michael G. Ross, Craig W. Blatz

Bibliographic record

VenueEuropean Journal of Social Psychology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsMacEwan UniversityUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIdeologyRedressPrivity of contractConservatismLiberalismSocial psychologySituational ethicsPolitical sciencePsychologyPoliticsLawEconomics

Abstract

fetched live from OpenAlex

Abstract In the legal literature, “privity” refers to the link between a minority's current social, psychological, and economic problems and its previous mistreatment by the government. Scholars speculate that judgments of privity underlie support for redress for historical injustices. There is no gold standard for evaluating privity, however, and its assessment is susceptible to personal and situational influences. We conducted three studies to examine how liberal‐conservative ideology interacts with group membership to predict judgments of privity and support for redress. This research is the first to examine the combined effects of liberal‐conservative ideology and group membership among respondents who belong to previously victimized minorities. Across both actual and hypothetical injustices, increasing conservatism was inversely related to judgments of privity, except when respondents were members of the victimized group. Victimized group members claimed privity regardless of ideology. The effects on support for reparations paralleled those for privity with one exception involving African Americans (Study 2). We discuss the implications of the findings for understanding the nature of liberalism‐conservatism. Copyright © 2013 John Wiley & Sons, Ltd.

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)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.060
GPT teacher head0.365
Teacher spread0.305 · 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 designObservational
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

Citations16
Published2013
Admission routes2
Has abstractyes

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