PARTICIPATORY RESEARCH METHODS FOR TECHNOLOGY EVALUATION: A MANUAL FOR SCIENTISTS WORKING WITH FARMERS
Bibliographic record
Abstract
This manual presents methods that enable agricultural scientist and farmers to \nevaluate technologies/practices jointly. The methods are specifically designed for \nparticipatory research on germplasm and soil fertility technologies, and they are illustrated \nwith actual examples from three research projects. The manual begins by reviewing \nconceptual issues that are important in participatory research and presents information to \nassist researchers in selecting research sites and fieldwork participants. Next, the manual \ndescribes the rationale and associated methods for each major activity in farmer participatory \nresearch: diagnosing farmers’ conditions, evaluating current and new technologies/practices, \nand assessing their impact. Goals, procedures, advantages, and limitations of each method are \noutlined. The manual also presents detailed information on analyzing data gathered through \nparticipatory methods, discusses differences between gathering data through participatory \nmethods and more traditional structured farm surveys, and offers examples, based on field \nexperience, of the choices and strategies involved in applying these methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".