Attributions of causality, responsibility and blame for positive and negative symptom behaviours in caregivers of persons with schizophrenia
Bibliographic record
Abstract
BACKGROUND: Causal, responsibility and blame attributions for positive and negative symptom behaviours were examined in 70 caregivers of persons with schizophrenia. METHODS: The majority of subjects belonged to self-help group organizations. The three types of attributions for positive and negative symptom behaviours were assessed by self-report questionnaires. RESULTS: The extent of patient responsibility did not differ between the two types behaviours. Intentionality and knowledge were equally important in predicting responsibility for positive symptom behaviours, while intent was the most important predictor of responsibility for negative symptom behaviours with the patient capacity playing a significant but minor role. The entailment model was not supported for the two types of behaviours. CONCLUSIONS: Increased attention should be given to responsibility dimensions in assigning moral accountability to the patient. The entailment model should be further explored in problematical caregiving situations.
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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 | 0.000 | 0.002 |
| 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 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".