Bibliographic record
Abstract
The purposes of this paper are: 1) to provide an overview of a participatory research approach as it maybe applied in health promotion in Japan. 2) to adapt guidelines for participatory research previously developed in Canada to the Japanese context. For this paper, we define participatory research as systematic inquiry, with the collaboration of those affected by the issue being studied, for purposes of education and taking action or effecting social change. Most definitions of participatory research emphasize the integration of three elements: research (usually described as systematic investigation), education and action. During a participatory research project, an educational and learning process takes place. The research process is also capacity building in that it enables and supports the development of new skills and expertise among both community participants and external researchers. Participatory research tries to bring together the search for solutions to community health problems and taking action by using a community development approach, within the research process. Participatory research is a process rather than a specific methodology. Quantitative and / or qualitative can equally be applied in participatory research. Descriptions of early projects in the development of participatory research stress an equal relationship between community members and technically trained researchers. Rather than presupposing absolute equality between the researcher and the community participants, more recent descriptions of participatory research emphasize the unique strengths and shared responsibilities of each group. Arai (1996) explains "A Key characteristic of participatory research is that the researcher understand the feelings and desires of community members, investigate and practice to solve their health issue." And participatory research uses their feelings and desires and also community members will have the assessment their abilities. The term community is defined in this context as any group of individual
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".