Hopping, skipping or jumping to conclusions? Clarifying the role of the JTC bias in delusions
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: There is substantial evidence that patients with delusions exhibit a reasoning bias--known as the "jumping to conclusions" (JTC) bias--which leads them to accept hypotheses as correct on the basis of less evidence than controls. We address three questions concerning the JTC bias that require clarification. Firstly, what is the best measure of the JTC bias? Second, is the JTC bias correlated specifically with delusions, or only with the symptomatology of schizophrenia? And third, is the bias enhanced by emotionally salient material? METHODS: To address these questions, we conducted a series of meta-analyses of studies that used the Beads task to compare the probabilistic reasoning styles of individuals with and without delusions. RESULTS: We found that only one of four measures of the JTC bias--"draws to decision"--reached significance. The JTC bias exhibited by delusional subjects-as measured by draws to decision--did not appear to be solely an epiphenomenal effect of schizophrenic symptomatology, and was not amplified by emotionally salient material. CONCLUSIONS: A tendency to gather less evidence in the Beads task is reliably associated with the presence of delusional symptomatology. In contrast, certainty on the task, and responses to contradictory evidence, do not discriminate well between those with and without delusions. The implications for the underlying basis of the JTC bias, and its role in the formation and maintenance of delusions, are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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