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Record W2085452177 · doi:10.1177/0146167214559709

Shared Identity Is Key to Effective Communication

2014· article· en· W2085452177 on OpenAlexfundno aff
Katharine H. Greenaway, Ruth G. Wright, Joanne Willingham, Katherine J. Reynolds, S. Alexander Haslam

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
FundersCanadian Institute for Advanced Research
KeywordsOutgroupSuperordinate goalsIngroups and outgroupsPsychologySocial psychologySocial identity theoryIdentity (music)Perspective (graphical)Social identity approachQuality (philosophy)Social groupEpistemology

Abstract

fetched live from OpenAlex

The ability to communicate with others is one of the most important human social functions, yet communication is not always investigated from a social perspective. This research examined the role that shared social identity plays in communication effectiveness using a minimal group paradigm. In two experiments, participants constructed a model using instructions that were said to be created by an ingroup or an outgroup member. Participants made models of objectively better quality when working from communications ostensibly created by an ingroup member (Experiments 1 and 2). However, this effect was attenuated when participants were made aware of a shared superordinate identity that included both the ingroup and the outgroup (Experiment 2). These findings point to the importance of shared social identity for effective communication and provide novel insights into the social psychology of communication.

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)0.003
metaresearch head score (Gemma)0.014
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.038
GPT teacher head0.394
Teacher spread0.356 · 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

Citations130
Published2014
Admission routes1
Has abstractyes

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