Stoecker, R., & Falcón, A. (Eds.). (2022). Handbook on participatory action research and community development. Edward Elgar Publishing.
Bibliographic record
Abstract
This book is laid out in six different sections.Part one explores the infrastructures that can support the integration of participatory action research (PAR) and community development (CD) effectively for community problem-solving and improvement.Part two focuses on organising communities, emphasising the importance of the community in working together towards change, making sense of community issues, and creating avenues for a systemic change.Part three explores the challenges of building organisations and empowering community by maintaining equitable and collaborative relationships with community stakeholders.Part four highlights the potential in youthdirected community level initiatives.Part Vive focuses on how power dynamics inVluence the incorporation of community development and participatory development practices, and how systematic collaborations can help respond appropriately to overcome crises.And part six illuminates the importance of covivencia, a beautiful Spanish term that describes the culture and signiVicance of living together in community, collaboration, and coexistence.Parts one, two, and three are particularly beneVicial to participatory action researchers as these sections articulate how participatory action research could be carried out in connection with community development to bring about systemic societal changes.However, part four plays a critical role in implementing PAR and CD as it illustrates the subtle nuances of collaborating with government authorities and highlights the importance of receiving funds for the interventions.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.024 |
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".