An environmental scan of methods for assessing age-friendliness in post-secondary institutions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The University of Calgary joined the Age-Friendly University (AFU) Global Network in 2018. As part of our university's AFU action plan, a baseline assessment of the institution's age-friendliness will be conducted to identify areas of strength and growth. To inform our approach and that of other institutions undertaking this work, an environmental scan was performed to determine methods used by post-secondary institutions to date to assess age-friendliness. Both academic and grey literature published between 2012 and 2022 in the English language was searched using diverse keywords. The academic literature was identified from four databases (Abstracts in Social Gerontology, Academic Search Complete, Education Research Complete, Scopus) and the grey literature from 84 institutional websites of AFU Global Network members. Twelve academic sources and four grey sources were included in the analysis. Seven methods were used to assess age-friendliness, with the most common approaches being surveys, inventories, focus groups, interviews, and photovoice. The Age-Friendly Inventory and Campus Climate Survey (Silverstein et al., 2022) was selected to evaluate the University of Calgary's age-friendliness due to its alignment with all 10 AFU principles, comprehensiveness, and involvement of multiple stakeholders. Other post-secondary institutions should consider their context and resources when selecting an assessment method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 it