Measures for Assessing Student Attitudes Toward Older People
Bibliographic record
Abstract
Measuring medical and allied health students' attitudes towards older people has been identified as an important research area. The present study compared the use of implicit and explicit attitude measures. Sixty-five undergraduates completed one explicit measure, the Fraboni Scale of Ageism (FSA), (Fraboni, Saltstone, & Hughes, 1990 Fraboni , M. , Saltstone , R. , & Hughes , S. ( 1990 ). The Fraboni Scale of Ageism (FSA): An attempt at a more precise measure of ageism . Canadian Journal on Aging , 9 , 56 – 66 .[Crossref], [Web of Science ®] , [Google Scholar]) and one implicit measure, the Implicit Association Test. They had positive explicit and neutral implicit attitudes towards older people, suggesting more positive attitudes than previously reported. These attitudes were related but there were discrepancies. Because explicit measures are likely to be influenced by factors such as social desirability, the implicit measure might be a more reliable measure.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".