Challenges of participatory research: reflections on a study with breast cancer self‐help groups
Bibliographic record
Abstract
OBJECTIVE: To review and discuss issues related to participatory research, as they apply within the arena of cancer control. DESIGN: A participatory research study with breast cancer self-help groups is referred to for description and discussion purposes. That study employed primarily individual and group interviews to assess benefits and limitations of self-help groups. SETTINGS: Four breast cancer self-help groups in Ontario communities provided the core involvement in the participatory research project. RESULTS: The values and practices of mainstream academic research often conflict with those of research emphasizing participation and control of communities under study, leading to a variety of challenges for the latter approaches. Practical constraints faced by many community groups have important implications for participatory research approaches. CONCLUSIONS: A balance needs to be found for participatory research within cancer control - one that ensures that the core aims of participatory research are maintained, while simultaneously acknowledging the various challenges that make a fully participatory project unrealistic. Steps can be taken to achieve a workable balance.
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 | 0.284 | 0.234 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.056 | 0.068 |
| Scholarly communication | 0.024 | 0.020 |
| Open science | 0.010 | 0.027 |
| Research integrity | 0.018 | 0.022 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".