More than just experts for hire: A conceptualization of the roles of consultants in public policy formulation
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 Consultants are increasingly a part of public policy formulation, and their policy involvement draws extensive interest in research and public debate. However, there is a gap in how we think about their formulation role: they are often conceptualized as a type of expert, while their actual interaction with and contribution to policy formulation is much more varied. This paper develops a conceptualization of consultants' formulation roles. It demonstrates that rather than just informing policy formulation, consultants take multiple roles and interact with policymaking and makers in multiple ways. Using a policy network/subsystem distinction and a substance/process distinction as the main axes for analysis, the paper develops four role categories: (1) experts and knowledge brokers, in which consultants provide policy advice and analysis; (2) seeing for the government, in which they construct a picture of the policy field; (3) legitimizers and validators, in which they provide symbolic capital to policy; and (4) channels for stakeholders' policy preferences, in which they manage deliberation and synthesize actors' policy preferences. The paper provides much‐needed clarity on how consultants engage with policy formulation and policymakers and forwards our understanding of how consultants exert their policy influence.
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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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