Bibliographic record
Abstract
One of the more notable—and well-noted—trends in public policymaking in Canada since the early 1980s has been a shift in the nature of policy advisory systems. The broadbrush strokes of this change paint a picture in which the closed dominance of professional public servants has been eroded in favour of more open, collaborative and inclusive systems. In these systems, civil society actors are now given an opportunity to play a much more extensive role in public policy analysis and advice. We have moved from a state-centric ‘vertical’ model towards a polycentric ‘horizontal’ one (Halligan, 1995; Craft & Howlett, 2013; Evans & Sapeha, 2015; Veselý, 2013; Atkinson et al., 2013; Bakvis, 2000; Savoie, 2003; Lindquist & Desveaux, 2007; Brooks, 2007; Mintrom, 2007; Prince, 2007; Phillips, 2007). This ‘externalization’ of policy advice has several manifestations, and includes the use of external consultants, think tanks, private research institutes, partisan political advisers, polling firms, universities, business and labour organizations, and other non-governmental organizations (Howlett & Migone, 2013; Craft & Howlett, 2013; Veselý, 2013; Atkinson et al., 2013; Howlett, 2015; Savoie, 2003; Speers, 2007; Abelson, 2007). It is sometimes traced back to the heyday of new public management (NPM) in the 1980s and early 1990s when budgetary constraints and a desire for streamlining dovetailed with a neoliberal restructuring of state functions (Bakvis, 2000; Speers, 2007; Evans & Wellstead, 2013; Voyer, 2007). Today, a “new governance” philosophy still persists and is articulated even at the centre of the Canadian federal bureaucracy. The Privy Council Office's 2016 Report to the Prime Minister on the Public Service of Canada touted an initiative to make the functioning of the public service, “even more collaborative, connected and open.” In the words of the Report: “It will be important never to return to a time where policy was developed in splendid isolation from the operations and services that implement it, or the people affected by it” (PCO, 2016, p. 18).
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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 | 0.021 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.034 | 0.019 |
| Scholarly communication | 0.030 | 0.008 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.004 |
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".