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Geographical Frame of Reference and Dangerous Intergroup Attitudes: A Double‐Minority Study in Sri Lanka

2006· article· en· W2102360396 on OpenAlexaff
Mark Schaller, Nilanga Abeysinghe

Bibliographic record

VenuePolitical Psychology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSri lankaTamilEthnic conflictEthnic groupSocial psychologySouth asiaPolitical scienceSalientInternally displaced personGender studiesPsychologySociologyEthnologyLaw

Abstract

fetched live from OpenAlex

An ethnic group can comprise a local majority, but be a minority within a broader geographic region or vice‐versa. This situation has interesting psychological implications that may contribute to intergroup conflict. To test some of these implications, an experiment was conducted in Sri Lanka, during a ceasefire in the conflict between the government and Tamil rebellion forces. Participants were 100 Sinhalese students. An experimental manipulation was introduced to make one of two geographical regions salient: either just Sri Lanka (within which Sinhalese outnumber Tamils) or a broader region of south Asia (within which Sinhalese are outnumbered by Tamils). Following the manipulation, stereotypes and conflict‐relevant attitudes were assessed. Results revealed that when Sinhalese participants were inclined to think of their group as the outnumbered minority, stereotypic perceptions of Tamils were more demonizing (i.e., depicting Tamils as more malevolent and also more competent), and their conflict‐relevant attitudes were less conciliatory. These results have conceptual implications as well as implications for understanding conflict and conflict resolution.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.352
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.064
GPT teacher head0.434
Teacher spread0.370 · 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.

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

Citations52
Published2006
Admission routes1
Has abstractyes

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