Expertise, policy advice, and policy advisory systems in an open, participatory, and populist era: New challenges to research and practice
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
Abstract This article examines the themes of policy advice, expertise, and policy advisory systems. It argues that persistent challenges and more emergent trends involving their intersection can be effectively understood through the lenses of instrumentality , authority , and adaptability . In the wake of renewed questions about the continued viability of longstanding public administration advisory arrangements, these themes help locate new pressures on those arrangement such as those linked to technological developments, shifting conceptions of expertise, and growing recognition of the challenges of managing systems of advice. These themes help facilitate continued engagement with persistent challenges linked to adequate policy capacity, the role of the public service advice, and question of rigour, legitimacy, and the democratic contexts of policy advising. Points for practitioners Technological innovations and turbulent governance arrangements have renewed debates around technocracy, democratic control and participation, the role of evidence, and normative and ethical considerations inherent in the generation and use of policy advice. Policy capacity remains important for well‐functioning policy advisory systems. It has itself become multifaceted reflecting not only important differences in types of expertise and policy advice, but also concerns around its management and deployment in varying governance contexts. The competencies required for policy workers inside and outside of government should reflect changes in the role of expertise and evolving systems of policy advice.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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