Routledge International Handbook of Participatory Approaches in Ageing Research
Bibliographic record
Abstract
This Handbook presents established and innovative perspectives on involving older adults as co-creators in ageing research. It reorients research and policy toward more inclusive and adequate designs that capture the voices and needs of older adults. The Handbook: introduces types of participatory approaches in ageing research; highlights key methodological aspects of these approaches; gives insights from projects across different cultural contexts and academic disciplines, showing ways in which older participants can be involved in co-designing different stages of the research cycle; examines key issues to consider when involving older participants at each step of the research process; includes the voices of older adults directly; draws out conclusions and points ways forward for future research. This Handbook will be essential reading for researchers and students interested in the field of ageing and/ or participatory methods, as well as for those policy stakeholders in the fields of ageing and demographic change, social and public policy, or health and wellbeing who are interested in involving older adults in policy processes. It will be useful for third-sector advocacy organizations and international non-governmental and public agencies working either in citizen involvement/participation or the ageing sector.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.095 | 0.060 |
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".