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Record W4386472703 · doi:10.33921/rgkx3539

Shared Stressful Situations and Affiliation in Stranger Dyads: An experimental Analysis

2023· article· en· W4386472703 on OpenAlexaffvenue
Atara Lonn, Cheryl Haramsymchuk

Bibliographic record

VenueJournal of Interpersonal Relations Intergroup Relations and Identity · 2023
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyFriendshipSituational ethicsSocial psychologyDevelopmental psychologyStressorContext (archaeology)Stress (linguistics)Clinical psychology

Abstract

fetched live from OpenAlex

According to the tend-and-befriend theory, shared stressors may create situations in which the inclination to interact with another person (i.e., immediate affiliative desire) is elevated. This may create a situational context in which sustained affiliative responses towards an interaction partner are more likely to occur in the longer-term. In the present study, we randomly assigned 85 undergraduate stranger dyads (N = 170 participants; all women) to either shared stress or shared control experiences and measured immediate affiliative desire. The strangers in the dyads then interacted with one another in a discussion task, and participants’ long-term affiliative responses (liking and future intentions to affiliate) were assessed. The evidence suggested that shared stressful experiences (vs. the shared control experiences) promoted significantly more immediate affiliative desire. Furthermore, immediate affiliative desire mediated the association between shared stress and long-term affiliative responses. These findings offer insight into how shared stress may influence friendship development.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
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 head0.024
GPT teacher head0.408
Teacher spread0.384 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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