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Record W2161726198 · doi:10.1177/0146167214551153

Overcoming the Barrier of Narrative Adherence in Conflicts Through Awareness of the Psychological Bias of Naïve Realism

2014· article· en· W2161726198 on OpenAlexfundno aff
Meytal Nasie, Daniel Bar‐Tal, Ruthie Pliskin, Eman Nahhas, Eran Halperin

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science Foundation
KeywordsNarrativeOpenness to experiencePsychologySocial psychologyContext (archaeology)AdversaryIdeologyRealismNarrative inquiryIdentification (biology)PoliticsEpistemologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

One significant socio-psychological barrier for peaceful resolution of conflicts is each party's adherence to its own collective narrative. We hypothesized that raising awareness to the psychological bias of naïve realism and its identification in oneself would provide a path to overcoming this barrier, thus increasing openness to the adversary's narrative. We conducted three experimental studies in the context of the Israeli-Palestinian conflict. Studies 1 and 2, conducted among Jewish Israelis and Palestinian Israelis, respectively, revealed that participants with hawkish political ideology reported greater openness to the adversary's narrative when they were made aware of naïve realism bias. Study 3 revealed that hawkish participants at the baseline adhered to the ingroup narrative and resisted the adversary's narrative more than dovish participants. They were also more able to identify the bias in themselves upon learning about it. This identification may explain why the manipulation led to bias correction only among hawkish participants.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.132
GPT teacher head0.416
Teacher spread0.283 · 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 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

Citations55
Published2014
Admission routes1
Has abstractyes

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