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On the interpersonal regulation of emotions: Emotional reliance across gender, relationships, and cultures

2005· article· en· W2139342546 on OpenAlexaff
Richard M. Ryan, Jennifer G. La Guardia, Jessica A. Solky-Butzel, Valery Chirkov, Youngmee Kim

Bibliographic record

VenuePersonal Relationships · 2005
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of SaskatchewanUniversity of Waterloo
Fundersnot available
KeywordsPsychologySocial psychologyAutonomySocializationInterpersonal communicationPerspective (graphical)Value (mathematics)Competence (human resources)Developmental psychology

Abstract

fetched live from OpenAlex

Abstract Three studies examine people's willingness to rely on others for emotional support. We propose that emotional reliance (ER) is typically beneficial to well‐being. However, due to differing socialization and norms, ER is also expected to differ across gender and cultures. Further, following a self‐determination theory perspective, we hypothesize that ER is facilitated by social partners who support one's psychological needs for autonomy, competence, and relatedness. Results from the studies supported the view that ER is generally associated with greater well‐being and that it varies significantly across different relationships, cultural groups, and gender. Within‐person variations in ER were systematically related to levels of need satisfaction within specific relationships, over and above between‐person differences. The discussion focuses on the adaptive value and dynamics of ER.

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)0.008
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
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 head0.190
GPT teacher head0.382
Teacher spread0.192 · 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

Citations282
Published2005
Admission routes1
Has abstractyes

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