Source monitoring and memory confidence in schizophrenia
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
BACKGROUND: The present study attempted to extend previous research on source monitoring deficits in schizophrenia. We hypothesized that patients would show a bias to attribute self-generated words to an external source. Furthermore, it was expected that schizophrenic patients would be overconfident regarding false memory attributions. METHOD: Thirty schizophrenic and 21 healthy participants were instructed to provide a semantic association for 20 words. Subsequently, a list was read containing experimenter- and self-generated words as well as new words. The subject was required to identify each item as old/new, name the source. and state the degree of confidence for the source attribution. RESULTS: Schizophrenic patients displayed a significantly increased number of source attribution errors and were significantly more confident than controls that a false source attribution response was true. The latter bias was ameliorated by higher doses of neuroleptics. CONCLUSIONS: It is inferred that a core cognitive deficit underlying schizophrenia is a failure to distinguish false from true mnestic contents.
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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) | 0.000 | 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 it