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Record W2000743628 · doi:10.1080/16506070701232090

Predictors of Post‐Event Rumination Related to Social Anxiety

2007· article· en· W2000743628 on OpenAlexaff
Nancy L. Kocovski, Neil A. Rector

Bibliographic record

VenueCognitive Behaviour Therapy · 2007
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoWilfrid Laurier University
Fundersnot available
KeywordsRuminationSocial anxietyPsychologyAnxietyCognitionAnxiety sensitivityDevelopmental psychologySocial inhibitionClinical psychologyEvent (particle physics)Psychiatry

Abstract

fetched live from OpenAlex

Post-event processing is the cognitive rumination that follows social events in cognitive models of social anxiety. The aim of this study was to examine factors that may predict the extent to which individuals engage in post-event processing. Anxious rumination, social anxiety, anxiety sensitivity and post-event processing related to a recent anxiety-provoking social event were assessed in a college student sample (n = 439). Social anxiety and anxious rumination, but not anxiety sensitivity, significantly predicted the extent to which the participants engaged in post-event processing related to an anxiety-provoking social event. Factors that appear to impact on the post-event period include the nature of the social situation and the ethnicity of the participant. It appears that both general rumination over anxious symptoms, and specific rumination related to social events are relevant for cognitive models of social anxiety.

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)0.008
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.028
GPT teacher head0.370
Teacher spread0.342 · 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

Citations111
Published2007
Admission routes1
Has abstractyes

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