Attitudes of medical clerks toward persons with intellectual disabilities.
Bibliographic record
Abstract
OBJECTIVE: To assess the attitudes of upper-year undergraduate medical students (ie, clerks) toward the philosophy of community inclusion of persons with intellectual disabilities (ID) according to demographic, personal contact, and training variables. DESIGN: Cross-sectional self-administered survey. SETTING: Clerkship rotations at Queen's University in Kingston, Ont, and the University of Toronto in Ontario in 2006. PARTICIPANTS: A total of 258 clerks. MAIN OUTCOME MEASURES: Scores on the Community Living Attitudes Scale-Short Form. RESULTS: There were no differences in the Community Living Attitudes Scale-Short Form subscale scores across categories of demographic characteristics, personal contact, or having received didactic training about ID. Clerks who had seen patients with ID during their medical school training had higher mean sheltering subscale scores than those who had not (3.27 vs 3.07, P = .02). Additional analysis revealed that 88.5% of clerks who had seen patients with ID reported seeing 5 or fewer such patients, and that those who rated the quality of their supervision more positively had higher mean scores on the empowerment subscale and lower mean scores on the sheltering subscale. CONCLUSION: Although specific training has the potential to promote more socially progressive attitudes regarding persons with ID, lower-quality supervision is associated with higher endorsement of items expressing the need to shelter individuals with ID from harm and lower endorsement of items promoting empowerment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".