Progress and future challenges in aging and diversity research in the United States
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
In 2016, the UC Davis Latino Aging Research Resource Center and UC Davis Alzheimer's Disease Center brought together experts from across the country to consolidate current knowledge and identify future directions in aging and diversity research. This report disseminates the research priorities that emerged from this conference, building on an earlier Gerontological Society of America preconference. We review key racial/ethnic differences in cognitive aging and dementia and identify current knowledge gaps in the field. We advocate for a systems-level framework for future research whereby environmental, sociocultural, behavioral, neuropathological, genetic, and psychometric levels of analysis are examined together to identify pathways and mechanisms that influence disparities. We then discuss steps to increase the recruitment and retention of racial/ethnic minorities in aging studies, as none of the recommendations will be possible without strong collaboration between racial/ethnic minority communities and researchers. This approach is consistent with the National Institute on Aging Health Disparities Research Framework.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it