The role of cognitive biases and personality variables in subclinical delusional ideation
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.
Bibliographic record
Abstract
INTRODUCTION: A number of cognitive biases, most notably a data gathering bias characterised by "jumping to conclusions" (JTC), and the "bias against disconfirmatory evidence" (BADE), have been shown to be associated with delusions and subclinical delusional ideation. Certain personality variables, particularly "openness to experience", are thought to be associated with schizotypy. METHODS: Using structural equation modelling, we examined the association between two higher order subfactors ("aspects") of "openness to experience" (labelled "openness" and "intellect"), these cognitive biases, and their relationship to subclinical delusional ideation in 121 healthy, nonpsychiatric controls. RESULTS: Our results suggest that cognitive biases (specifically the data gathering bias and BADE) and the "openness" aspect are independently associated with subclinical delusional ideation, and the data gathering bias is weakly associated with "positive schizotypy". "Intellect" is negatively associated with delusional ideation and might play a potential protective role. CONCLUSIONS: Cognitive biases and personality are likely to be independent risk factors for the development of delusions.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it