Duplicative or Complementary? The Relationship between Policy Consulting and Internal Policy Analysis in Canadian Government
Bibliographic record
Abstract
Abstract Policy consultants are external analysts who provide paid policy-related advice to governments on a contractual basis. Previous research on policy work has examined the work done within governments and by policy consultants separately but has not systematically compared and contrasted the two. A key question regarding the nature of policy advisory practices and policy advice systems in general, however, is whether consultants are duplicating the work of government officials in order to help “triangulate” internal advice or whether there is more of a complementary approach in which consultants supplement the work of internal analysts. This article explores the differences among the two groups using data collected over the past five years in two sets of surveys into internal and external policy work in Canada. The analysis finds a “complementary” relationship to exist, contrary to the conventional wisdom that outside or external advice is sought mainly in order to avoid biases in internal advice.
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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 | 0.032 | 0.213 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.026 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".