HISTORICAL OVERVIEW OF BRIDGING AGING AND DISABILITY RESEARCH AND POLICY – U.S. AND INTERNATIONAL MILESTONES
Bibliographic record
Abstract
World-wide changing demographics reflected in both increased longevity and chronic disability, combined with competing demand for scarce resources, have contributed to a growing recognition of the shared needs and preferences of older adults and people aging with disabilities for community based services and supports, including technologies for independence. These trends, first articulated in the U.S. over 30 years ago, have led to evolving interest in finding ways to reduce the silos between aging and disability fields by bridging policy, research and practice to better serve middle-aged and older adults living with the effects of long-term impairments and disabilities. This presentation will define the concept of bridging and trace the historical origins and demographic context of key milestones of bridging within the U.S. and internationally, starting in the U.S. with early federal funding initiatives, the Supreme Court’s Olmstead Decision of 1999 and the establishment of the Aging and Disability Resource Centers under the Administration on Aging and path-breaking developments in European and Canada.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".