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Record W3043009920 · doi:10.1177/0265407520939191

“How do you like them now?” Expected reactions upon discovering that a friend is a political out-group member

2020· article· en· W3043009920 on OpenAlexaff
Elena Buliga, Cara C. MacInnis

Bibliographic record

VenueJournal of Social and Personal Relationships · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFriendshipPoliticsSocial psychologyPsychologyGroup (periodic table)Political scienceLaw

Abstract

fetched live from OpenAlex

Republican or Democrat participants imagined how they would respond upon learning about the political group membership of a potential or established friend. Four vignettes (friend political in-group; friend political out-group; potential friend political in-group; potential friend political out-group) were presented in a random order. After each, participants provided expected reactions. Overall, reactions (e.g., hope of the relationship lasting, intentions to engage in friendship maintenance behaviors, trust) were most positive toward the established in-group friend, followed by potential in-group friend, then the established out-group friend, and lastly the potential out-group friend. That is, participants expected to be more positive toward a person they just met than an established close friend, simply due to knowing these individuals’ political group memberships. Some of these differences were moderated by intergroup attitudes or political identification. Discoveries of political group membership may influence the development or maintenance of friendships.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.184
GPT teacher head0.352
Teacher spread0.168 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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