Policy advice through the market: The role of external consultants in contemporary policy advisory systems
Bibliographic record
Abstract
Abstract The use of external policy consultants in government has been an increasing focus of concern among governments in the U.S., the UK, Canada and Australia, among others. Concern has arisen over the costs incurred by governments in this area and over the possible rise of a ‘consultocracy’ with the corresponding diminishment of democratic practices and public direction of policy and administrative development that could entail. However, current understanding of the origins and significance of the use of policy consultants in modern government is; poor with some seeing this development as part of a shift in the overall nature of state-societal relations to the ‘service’ or ‘franchise’ state and away from the ‘positive’ or ‘regulatory’ state, while others see it as a less significant activity linked to the normal development of policy advice systems in modern government. This article surveys the existing literature on the phenomena, in general, and identifies several methodological and data-ralated issues germane to the study and understanding of the activities of this set of external policy advisory system actors.
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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 | 0.044 | 0.099 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.014 | 0.030 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".