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Intercultural Conflict and Mediation: An Intergroup Perspective

2012· article· en· W1551604198 on OpenAlexaffabout
Sara Rubenfeld, Richard Clément

Bibliographic record

VenueLanguage Learning · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologyMediationSocial psychologyPerspective (graphical)Context (archaeology)Group conflictMediatorSociology

Abstract

fetched live from OpenAlex

This study investigates the role of components of intercultural competence in the use of intercultural mediation behaviors. Through the use of the Revised Intercultural Mediation Measure, an instrument revised by the authors, 291 Anglophone and 161 Francophone participants in Canada were asked to indicate their likelihood of employing various mediation strategies to reduce a conflict between two linguistic groups. The results demonstrated that involvement as an intercultural mediator is likely to be initiated by individuals who are members of the same linguistic group as the perpetrator. By virtue of their xenophilic representations of the victimized group, these individuals take on the role of mediator to reduce tension. In contrast, participants from both linguistic groups were unlikely to become involved as a mediator when witnessing members of the in‐group being victimized. Furthermore, path analyses revealed that the use of mediation strategies when the in‐group was being discriminated against was, at most, limited to endorsing fewer avoidant mediation strategies. The findings are interpreted within the context of research on intergroup relations and discrimination.

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)0.006
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.010
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.382
Teacher spread0.358 · 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

Citations10
Published2012
Admission routes2
Has abstractyes

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