Positive schizotypy is not associated with speech abnormality
Bibliographic record
Abstract
AIM: This study examined whether speech abnormalities typical of formal thought disorder in schizophrenia vary with the degree of positive schizotypy in the healthy population. We hypothesized that participants with high levels of positive schizotypy would show greater abnormality in speech relative to those with low levels of positive schizotypy. METHODS: Participants (n=107) were prescreened with a positive schizotypy scale. Those meeting criteria for either high (n=23) or low (n=27) schizotypy provided speech samples which were assessed with a clinical though disorder rating scale (Thought and Language Index) for the presence of abnormality. RESULTS: No significant differences were found in positive (P=0.25) or negative (P=0.21) speech abnormality between the high and low schizotypy groups. CONCLUSION: Although schizotypy is normally distributed in the general population, speech abnormality is not. Thus, the presence of aberrations in speech may predict risk of psychosis. Potential implications for risk assessment are discussed.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".