Beyond consultocracy and servants of power: Explaining the role of consultants in policy formulation
Bibliographic record
Abstract
Abstract Prior research on consultants in policymaking described their expanding policy involvement and impact. This research focuses on consultants' policy formulation roles and on how and why these roles vary across jurisdictions and contexts. It draws on comparative research on healthcare policy in Ontario, Canada, and Victoria, Australia. Based on analysis of contracts and expenditure data, and 59 semi‐structured interviews, this research finds that consultants in Victoria are partners in formulation, used routinely for a variety of tasks, including core formulation work. Their role is institutionalized through formal and informal rules. In contrast, consultants in Ontario perform non‐core formulation work and are primarily active in linking the government to other sites and pools of knowledge. The paper ties this variation to public sector internal capacity and policy sector complexity. It offers new empirical data and provides a nuanced understanding of the roles of consultants in policy formulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.012 | 0.045 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".