COMPETENCIES IN EUROPEAN GERONTOLOGICAL HIGHER EDUCATION. AN EXPLORATIVE STUDY ON CORE ELEMENTS
Bibliographic record
Abstract
This study explores whether there is a common core of competencies in European gerontology education programs by doing a cross-comparison of five undergraduate level programs. Content analysis of competency profile documents at the five European educational programs were studied using thematic analysis. Study results document that there indeed is a common core of elements in gerontological educational programs. Three clusters which included a total of fifteen categories were identified. The clusters were labeled professional attitude, communication skills and service provision. Clusters and categories varied across the five programs. One program in particular included less clusters and categories. This may reflect a difference in focus in the program, but could also reflect a less elaborately formulated competency profile document. The results of this study show that, at the level of formulating competencies, there is a strong agreement on the major components that are important for a gerontologist at the undergraduate level.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".