Ageism Across Cultures and Interest in Geropsychology Among International Students
Bibliographic record
Abstract
Abstract Ageist attitudes are concerning when considering who will enter the geriatric workforce. The impact of ageism on intent to work with older adults (OAs) between North American and non-North American individuals is unclear. We collected data from N=186 students (n=153 N. American, n=33 non-N. American), examining ageist attitudes and intent to work with OAs. We found significant differences between groups in ageist attitudes; North American students had more positive views of aging (M=88.64, SE=0.72) than non-North American students (M=85.33, SE = 1.42; t (167) = 2.04, p = 0.04, d=0.39), but there were no differences between groups for intent to work with OAs (t (174) = 0.09, p = 0.93). Ageist attitudes predicted intent to work with OAs for North American students only (F (2, 112) = 8.82, p < 0.001, R2 = 0.14). We discuss implications of ageism and intent to work with OAs from a cross-cultural lens.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".