Policy Consulting in the USA: Significant but in Decline?
Bibliographic record
Abstract
As the Introduction to this book has argued, governmental use of consultancy services has long been a concern for scholars of public administration, management and political science (Howlett and Migone 2013a, 2013b; Kipping and Engwall 2003; Graeme and Bowman 2006; Guttman and Willner 1976; Rosenblum and McGillis 197).Although the impact of policy consulting is generally expected to be fairly broad, most of these studies have focused on a narrow set of questions related to the effect of contracting out on levels of public service employment and budgets (Dilulio 2016; Guttman and Willner 1976; GAO 2011) rather than on policy outcomes. Much existing research has focused either on placing this expansion in a historical perspective (McKenna 1995, 1996, 2006), or assessing its underlying causes and consequences (David 2012; Berit and Kieser 2002; McGann 2007).
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".