Assessing the ‘forgotten fundamental’ in policy advisory systems research: Policy shops and the role(s) of core policy professionals
Bibliographic record
Abstract
During the past 30 years, research on policy analytical capacity's multidimensional nature and the evolution of policy advisory systems (PASs) has both increased knowledge of these processes and structures and opened new avenues of inquiry. While it is clear that changes in PASs in many countries have occurred - featuring processes such as the increased externalisation and politicisation of policy advice - studies of changes among the roles played by core policy professionals in advice provision have lagged. One aspect of this question concerns the nature and extent of changes in this ‘forgotten fundamental’ of advice systems related to how these professionals are arrayed within ‘policy shops’—that is organisational units identified in the 1960s and 1970s as the main organisational home of policy professionals in government. Whether or not such shops have changed from the central-integrated model identified in early studies and, if so, how, remain outstanding and foundational questions. Recent research in Canada has mapped the distribution of policy professionals at the central and provincial level and found more types of analysts and venues than in earlier eras— which range from the ‘classical’ integrated policy shops of the 1960s and 1970s which remain in central agencies and single-purpose line departments to the much more 'distributed' patterns found in many departments dealing with multiple or complex controversial issues. Using Canadian data, this study outlines the development of these organisational types and their distribution in government and discusses the implications of these changes for better understanding the work, and needs, of core professionals in policy advice systems. .
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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 | 0.100 | 0.172 |
| Meta-epidemiology (narrow) | 0.000 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.020 | 0.080 |
| Scholarly communication | 0.028 | 0.031 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".