Rights and knowledge-based approach to aging and disability: an overview of issues and approaches
Bibliographic record
Abstract
This analysis paper is part of a larger project led by the Canadian Centre on Disability Studies (CCDS) and funded by Human Resources and Social Development Canada (HRSDC), called “From Research and Knowledge to Better Practice: Building Strategies and Partnerships for Livable Communities That are Inclusive of Seniors with Disabilities” (2008-09). The central purpose of the larger project was to develop and test a model of livable and inclusive communities that includes the needs, preferences, and circumstances of seniors with disabilities. A participatory method was used to accomplish this goal by identifying the key principles and elements of what makes communities livable and inclusive for seniors with disabilities and to develop and test a Livable and Inclusive Community Evaluation Tool and process to measure the extent to which the community meets their needs. In addition, a Livable and Inclusive Community Planning Tool was developed and introduced to several pilot communities across Canada. This paper provides an overview of issues, needs and approaches to disability and aging and is the beginning of the subsequent series of papers. In this discussion the terms “seniors” and “older adults” are used interchangeably refl ecting the fl exible use of the terms in the North American context.
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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 | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".