SUPPORT Tools for evidence-informed health Policymaking (STP) 14: Organising and using policy dialogues to support evidence-informed policymaking
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
This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers. Policy dialogues allow research evidence to be considered together with the views, experiences and tacit knowledge of those who will be involved in, or affected by, future decisions about a high-priority issue. Increasing interest in the use of policy dialogues has been fuelled by a number of factors: 1. The recognition of the need for locally contextualised 'decision support' for policymakers and other stakeholders 2. The recognition that research evidence is only one input into the decision-making processes of policymakers and other stakeholders 3. The recognition that many stakeholders can add significant value to these processes, and 4. The recognition that many stakeholders can take action to address high-priority issues, and not just policymakers. In this article, we suggest questions to guide those organising and using policy dialogues to support evidence-informed policymaking. These are: 1. Does the dialogue address a high-priority issue? 2. Does the dialogue provide opportunities to discuss the problem, options to address the problem, and key implementation considerations? 3. Is the dialogue informed by a pre-circulated policy brief and by a discussion about the full range of factors that can influence the policymaking process? 4. Does the dialogue ensure fair representation among those who will be involved in, or affected by, future decisions related to the issue? 5. Does the dialogue engage a facilitator, follow a rule about not attributing comments to individuals, and not aim for consensus? 6. Are outputs produced and follow-up activities undertaken to support action?
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.
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 | 0.042 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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