International Perspectives in Participatory Research and Evaluation
Bibliographic record
Abstract
This new course is the result of an exciting collaboration between the Society for Participatory Research in Asia (PRIA) located in India and the University of Victoria, located in British Columbia, Canada. The course was conceived to share insights developed from both the Non-Governmental Organisation (NGO) world and the University world, and was designed by practitioners from both India and Canada. It is our hope that it will be useful to adult educators, community development workers, activists, and NGO staff in any part of the world. International Perspectives in Participatory Research is an introduction to the practice and theory of community-based participatory research (PR) and evaluation (PE) from global perspectives. The emphasis is on the role of participatory research and evaluation in adult learning, community action, and community transformation. Examples will be drawn from international case studies. Issues of partnership, degrees of participation, and guidelines for practice will be featured, along with artistic ways of creating and representing knowledge in a community-based context. International Perspectives in Participatory Research is offered by the University of Victoria’s Certificate in Adult and Continuing Education (CACE) program, and is open to non-CACE students.
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 | 0.344 | 0.190 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.010 | 0.042 |
| Scholarly communication | 0.024 | 0.016 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".