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Record W2020533476 · doi:10.1017/s1742058x09090080

CHANGE WE CAN BELIEVE IN?

2009· article· en· W2020533476 on OpenAlexaff
Richard P. Eibach, Valerie Purdie‐Vaughns

Bibliographic record

VenueDu Bois Review Social Science Research on Race · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWhite (mutation)Polarization (electrochemistry)PerceptionRacial equalityPolitical scienceSocial psychologyRacismGender studiesSociologyPsychology

Abstract

fetched live from OpenAlex

Abstract Barack Obama's election as the first Black president of the United States has stimulated much discussion about progress toward racial equality in the United States. Opinion surveys document that White Americans reliably perceive the rate of progress toward racial equality as greater than do Black Americans. We focus on two psychological factors that contribute to these diverging perceptions: (1) the tendency of White Americans and Black Americans to adopt different reference points to assess racial progress, and (2) the general tendency to frame social change as a zero-sum game in which Black Americans' gains entail losses for White Americans. We review research examining how these two factors contribute to racial polarization on the topic of progress toward equality. We also draw on excerpts from Barack Obama's speeches and writings to demonstrate that he often frames issues in ways that, our research suggests, has the potential to substantially bridge these racial divisions.

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)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.016
Scholarly communication0.0080.008
Open science0.0010.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0170.004

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 head0.247
GPT teacher head0.546
Teacher spread0.299 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations11
Published2009
Admission routes1
Has abstractyes

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