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Record W4283747405 · doi:10.1177/21676968221111316

Co-Rumination in Social Networks

2022· article· en· W4283747405 on OpenAlexaff
Samantha M. Jones, Erin A. Heerey

Bibliographic record

VenueEmerging Adulthood · 2022
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsWestern University
Fundersnot available
KeywordsRuminationPsychologySocial psychologyDevelopmental psychologyCognition

Abstract

fetched live from OpenAlex

Although co-rumination is associated with positive relationship perceptions, individuals that engage in this behaviour often report fewer friends and peer difficulties. Those with a tendency to co-ruminate also report elevated levels of internalizing symptoms. Thus, the tendency to co-ruminate may put individuals at risk of depressive and anxious symptoms as well as social problems as they make the challenging transition to university and build new social networks. I analyzed social network data from 458 first year undergraduate students during their first university semester. Co-rumination within a particular relationship was associated with greater tie strength and socio-emotional multiplexity. Co-rumination was positively associated with depressive and anxious symptoms. Contrary to predictions, individuals with a tendency to co-ruminate did not differ from their peers in terms of network size and density. Results suggest that the negative impacts of co-rumination on social well-being may develop over time, rather than being apparent in the early stages of network building.

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)0.013
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.357
Teacher spread0.331 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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