What we have learnt (so far) about deliberative dialogue for evidence-based policymaking in West Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Policy decisions do not always take into account research results, and there is still little research being conducted on interventions that promote their use, particularly in Africa. To promote the use of research evidence in Africa, deliberative dialogue workshops are increasingly recommended as a means to establish evidence-informed dialogue among multiple stakeholders engaged in policy decision-making. In this paper, we reflect on our experiences of conducting national workshops in six African countries, and we propose operational recommendations for those wishing to organise deliberative dialogue. Our reflective and cross-sectional analysis of six national deliberative dialogue workshops in which we participated shows there are many specific challenges that should be taken into account when organising such encounters. In conclusion, we offer operational recommendations, drawn from our experience, to guide the preparation and conduct of deliberative workshops.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it