How long-term emancipatory programming facilitates participatory evaluation: Building a methodology of participation through research with youth in Honduras
Bibliographic record
Abstract
Empowerment and participation are promoted as critical factors in meaningful development processes; however, action-oriented researchers face challenges in fostering genuine empowerment and meaningful participation within traditional funding cycles and research timelines. This case study illustrates a participatory methodology employed by researchers in partnership with one Honduran non-governmental organization (NGO) to conduct 'practical' participatory evaluation with rural Honduran youth. Through collaborative autoethnography, two components of this methodology are identified and described. The first component - 'foundational elements'- includes the NGO's culture of transformative participation and the organization's attention to synergies in the insider/outsider identities of research partners. The second component includes the ability of the research team to leverage this foundation for the participatory evaluation with rural youth. Importantly, this ability was grounded in and shaped by long-term, trust-based relationships between research partners. These relationships were the catalyst for success in this participatory initiative, connecting the 'foundational elements' identified to the collaborative outcomes experienced. Overall, this case study contributes to current and ongoing scholarly discussions on how to facilitate meaningful participation and capability expansion in research and evaluation contexts.
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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 | 0.065 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".