Bibliographic record
Abstract
Introduction For close to a century, public policy research institutes, or think tanks as they are often described in the mainstream media and in the academic literature, have made their presence felt on the Canadian political landscape. Although the largest concentrations of think tanks can be found in the United States, most advanced and developing countries count them among the many types of non-governmental organizations that engage in research and analysis. Along with interest groups, trade associations, human rights organizations, advocacy networks and a handful of other bodies, think tanks rely on their expertise and knowledge to influence public opinion and public policy. What has distinguished think tanks in the past, particularly those that came of age during the early decades of the twentieth century, from the other organizations mentioned above, is their reputation for being objective, scientific and non-partisan. However, in recent decades, as think tanks have invested considerable resources in shaping public opinion and public policy, their image as scholarly and policy-neutral organizations has been called into question. Indeed, it has become increasingly difficult to differentiate between think tanks, lobbyists, government relations firms, consultants and interest groups. As think tanks have come to occupy a stronger presence in the policymaking community, academic interest in their role and function has intensified. While some scholars (Rich, 2004; Abelson, 1996; 2006; 2009; Stone, 1996; McGann, 1995; 2016; Ricci, 1993; Smith, 1991; Weaver, 1989) have been preoccupied with how and to what extent think tanks have been able to access the highest levels of the American government, others have paid close attention to the various ways in which think tanks have tried to make an impact in Westminister parliamentary democracies such as Canada (Abelson, 2016) and Great Britain (Savoie, 2003; Baier & Bakvis, 2001; Lindquist, 1998; Dobuzinskis, 1996). This research has led to several comparative studies in the field (Stone and Denham, 2004; 1998; McGann & Weaver, 2000; Pautz, 2012; Abelson et al., 2017), which have focused on, among other things, the extent to which different political systems facilitate or frustrate the efforts of think tanks to participate in the policymaking process. For example, some recent studies (Abelson, 2009; 2016; Abelson & Carberry, 1998) have tried to explain why American think tanks enjoy far more visibility and prominence than their Canadian counterparts.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.040 | 0.019 |
| Scholarly communication | 0.023 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.020 | 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".