Thinking high but feeling low: An exploratory cluster analysis investigating how implicit and explicit spider fear co-vary
Bibliographic record
Abstract
Research has demonstrated large differences in the degree to which direct and indirect measures predict each other and variables including behavioural approach and attentional bias. We investigated whether individual differences in the co-variance of "implicit" and "explicit" spider fear exist, and whether this covariation exerts an effect on spider fear-related outcomes. One hundred and thirty-two undergraduate students completed direct and indirect measures of spider fear/avoidance, self-report questionnaires of psychopathology, an attentional bias task, and a proxy Behavioural Approach Task. TwoStep cluster analysis using implicit and explicit spider fear as criterion variables resulted in three clusters: (1) low explicit/low implicit; (2) average explicit/high implicit; and (3) high explicit/low implicit. Clusters with higher explicit fear demonstrated greater disgust propensity and sensitivity and less willingness to approach a spider. No differences between clusters emerged on anticipatory approach anxiety or attentional bias. We discuss results in terms of dual-systems and cognitive-behavioural models of fear.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".