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Record W3179165981 · doi:10.1111/bjso.12481

Communicating group norms through election results

2021· article· en· W3179165981 on OpenAlexaff
Lily Syfers, Amber M. Gaffney, David E. Rast, Dennis A. Estrada

Bibliographic record

VenueBritish Journal of Social Psychology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLegitimacyNormativePerceptionSocial psychologyDemocracyIdentity (music)Democratic legitimacyVotingSocial identity theoryPsychologyPolitical scienceCollective identitySocial groupLawPolitics

Abstract

fetched live from OpenAlex

In a representative democracy, leaders (ideally) who are elected through the electorates should indicate consensus that the newly elected leader truly does represent the majority of the nation or the group. That is, once elected, can the ensuing perceptions of the electorate's consensus provide the newly elected leader with a sense of legitimacy and the ability to represent the group? Two experiments demonstrate that the perceptions of group consensus stemming from democratic elections can imbue newly elected leaders (even if they were once deviant) with legitimacy. Study 1 (N = 158) demonstrates that normative leaders are perceived as more legitimate than deviant leaders when elected with high voting consensus, which increased the perceived prototypicality of the normative leader through greater perceptions of legitimacy. Study 2 (N = 182) showed that newly elected leaders (vs. candidates) are perceived as more legitimate, which in turn, increases the group's perceptions of the once deviant leader's prototypicality, granted that the leader is democratically elected. Results suggest that democratic elections create conditions under which once deviant leaders can gain in perceived prototypicality and create lasting changes to the group identity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.582
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.404
Teacher spread0.353 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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