DELIBERATIVE DIALOGUES: OPPORTUNITIES FOR BRIDGING GERONTOLOGICAL RESEARCH WITH POLICY AND PRACTICE
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
Deliberative dialogues is a methodology that provides an integrated framework for concurrently generating and analyzing data, engaging participants, and synthesizing evidence. This methodology offers an important opportunity to bridge gerontological research with policy and practice and can lead to community investment and asset sharing by integrating the knowledge and experiences of multiple stakeholder groups. This symposium will present work from researchers representing the Behavioral and Social Sciences and Social Research, Policy, and Practice Research sections. The papers presented are based on a collection of research projects in Western Canada that explore different aspects of service and housing provision for seniors. Battersby et al. present World Café workshop findings from dialogues with housing providers who have had experience with mass interinstitutional relocations in long-term care. Fang et al. report on Perspectives Workshops with service providers that resulted in findings which informed services and programs offered to tenants of a low-income seniors’ rental property. Canham et al. discuss methods of engagement with Housing First seniors’ service providers during a Mapping Workshop and will report findings of available Housing First resources and where there are service gaps. Finally, Wada et al. highlight findings from an interactive research engagement with knowledge users and research participants at the end of a two-year evaluation project during a Research Day. To conclude this symposium, our discussant will summarize the papers using an interdisciplinary perspective and will discuss the implications of using innovative methods in bridging policy and practice.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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