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Record W2128899942 · doi:10.5539/ijps.v5n1p31

Differential Responses of Independent and Interdependent People to Social Exclusion

2013· article· en· W2128899942 on OpenAlexvenueno aff
Ken’ichiro Nakashima, Taishi Kawamoto, Chikae Isobe, Mitsuhiro Ura

Bibliographic record

VenueInternational Journal of Psychological Studies · 2013
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsnot available
Fundersnot available
KeywordsInterdependencePsychologySocial psychologyInterpersonal communicationInterpersonal relationshipIdentification (biology)Self construalSocial exclusionSocial relationInterpersonal interactionSociology

Abstract

fetched live from OpenAlex

To what extent is a person’s interpersonal network mustered after social exclusion? This was investigated inrelation to self-construal: independent, or interdependent. We conducted two quasi-experimental questionnairestudies of university students (Study 1; N = 57, Study 2; N = 78). Results indicated that interdependent studentslowered identification with their academic departments after remembering a time when they were sociallyexcluded (Study 1). Their self-worth was also more highly contingent on relational harmony in the whole of theirinterpersonal networks (Study 2). In contrast, independent students did not exhibit these patterns. These resultssuggest that social exclusion caused interdependent (not independent) individuals make attempts to secure andvalue their entire networks, due to the possibility that such specific identification might actually serve to limitpossible interpersonal networks (boundary effect). It is concluded that independent and interdependent studentsevidence dissimilar responses to social exclusion. The implications of this finding are discussed.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.425
Teacher spread0.363 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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