Grey Matters: A Guide for Collaborative Research with Seniors
Bibliographic record
Abstract
This study marks a major step in making collaboration between seniors, academic researchers, and community researchers a reality. Many aging adults are motivated to undertake research projects in later life or even return to university after retirement. Grey Matters is the result of a pilot project developed to study the effectiveness of collaborative research involving seniors. Because the project was such a success, the authors were encouraged to make their model available both to seniors interested in undertaking their own research and to those hoping to involve seniors in collaborative research. This guide provides a helpful framework for making the most of research projects by and with seniors, including sections on such techniques as narrative interviews, focus groups, and surveys. Grey Matters will be the first Open Access book published by the University of Calgary Press. On October 22, 2010, it will be released simultaneously in traditional print book format and as a free downloadable PDF file from this website.
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.
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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.052 | 0.072 |
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".