The Article Idea Chart: A participatory action research tool to aid involvement in dissemination
Bibliographic record
Abstract
Participatory-action research encourages the involvement of all key stakeholders in the research process and is especially well suited to mental health research. Previous literature outlines the importance of engaging stakeholders in the development of research questions and methodologies, but little has been written about ensuring the involvement of all stakeholders (especially non-academic members) in dissemination opportunities such as publication development. The Article Idea Chart was developed as a specific methodology for engaging all stakeholders in data analysis and publication development. It has been successfully utilised in a number of studies and is an effective tool for ensuring the dissemination process of participatory-action research results is both inclusive and transparent to all team members, regardless of stakeholder group.Keywords: participatory-action research, mental health, dissemination, community capacity building, publications, authorship
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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 | 0.109 | 0.167 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".