Are we leaving someone behind? A critical discourse analysis on the understanding of public participation among people with experiences of participatory research
Bibliographic record
Abstract
Participatory research (PR) is on the rise. In Spain, PR is scarce in the field of health, although there is an increasing interest in the matter. A comprehensive understanding of the meanings and practical implications of "public participation" is essential to promote participation in health research. The aim of the study is to explore the discursive positions on PR among individuals with experience in participatory processes in different areas and how this understanding translates into practice. We conducted a critical discourse analysis of 21 individuals with experience in PR and participatory processes (13 women, 8 men), mainly from the field of health and other areas of knowledge. Sixteen were Spanish and the rest were from the United Kingdom (3), United States (1), and Canada (1). Interviews were conducted in person or by telephone. The fieldwork was conducted between March 2019 and November 2019. The dominant discourses on public participation are situated along two axes situated on a continuum: the purpose of public participation and how power should be distributed in public participation processes. The first is instrumental public participation, which sees participatory research as a tool to improve research results and focuses on institutional interests and power-decision making is hold by researchers and institutions. The second, is transformative public participation, with a focus on social change and an equitable sharing of decision-making power between the public and researchers. All discursive positions stated that they do not carry out specific strategies to include the most socially disadvantaged individuals or groups. A shift in the scientific approach about knowledge, along with time and resources, are required to move towards a more balanced power distribution in the processes involving the public.
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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 | 0.059 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.026 | 0.065 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".