Interrelationships between spider fear associations, attentional disengagement and self-reported fear: A preliminary test of a dual-systems model
Bibliographic record
Abstract
Recent conceptualisations of anxiety posit that equivocal findings related to the time-course of disengaging from threat-relevant stimuli may be attributable to individual differences in associative and rule-based processing. The current study was designed to test the hypothesis that strength of spider-fear associations would indirectly predict reported spider fear via impaired disengagement. One hundred and thirty-one undergraduate volunteer participants completed the Go/No-go Association Task, a visual search task, and self-report spider fear questionnaires. Stronger spider-fear associations were associated with reduced disengagement accuracy, whereas higher levels of reported spider fear were related to faster engagement with and disengagement from spiders. Bootstrapping multiple mediation analyses demonstrated that stronger-spider fear associations evidenced an indirect relationship with reported spider fear via reduced disengagement accuracy, highlighting the importance of fine-grained analyses of different aspects of cognitive bias. Results are discussed in terms of cognitive models of anxiety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".