MétaCan
Menu
Back to cohort
Record W1989506021 · doi:10.1521/jscp.2011.30.2.105

Danger Appraisals as Prospective Predictors of Disgust and Avoidance of Contaminants

2011· article· en· W1989506021 on OpenAlex
Nicole M. Dorfan, Sheila R. Woody

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Social and Clinical Psychology · 2011
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDisgustPsychologyAnxietyNeuroticismSubclinical infectionCognitionDevelopmental psychologyClinical psychologySocial psychologyPersonalityPsychiatryAnger

Abstract

fetched live from OpenAlex

Although several cognitive theories have proposed specific types of appraisals hypothesized to increase fear and avoidance of contaminants, little research has tested these ideas. The current study utilized a prospective design to assess appraisals and dispositional traits in a normal sample several days prior to a behavioral approach task (BAT) involving commonly-encountered contamination stimuli. Danger appraisals significantly predicted behavioral avoidance and self-reported disgust, but not anxiety, during the BAT, even after accounting for neuroticism, disgust sensitivity, and subclinical obsessive-compulsive symptoms. The prospective design of the study establishes temporal precedence of danger appraisals, assessed during a period of low emotion, predicting subsequent emotional and behavioral response. Results also point to the importance of disgust sensitivity and the experience of disgust in response to everyday contaminants. These findings are discussed in light of public health outbreaks including Severe acute respiratory Syndrome (SARS) and the H1N1 flu, which have caused novel contamination threats worldwide in recent years.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.247
GPT teacher head0.436
Teacher spread0.189 · 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