Federalism and Public Responsiveness to Policy
Bibliographic record
Abstract
Public responsiveness to government policy is a crucial component of representative democracy, but may be far weaker in federal regimes.This article explores the consequences of federalism for public responsiveness in one highly federalized policy domain: welfare spending in Canada. Results suggest that citizens’preferences for spending at the federal level are affected by changes in both federal and provincial spending, and to an equal degree; they suggest, in short, that federalism poses serious problems where public responsiveness is concerned. A concluding section considers the implications of these findings for the representation of public opinion in policy in federalized states. Recent years have seen an increase in federalism and other forms of decentralization worldwide (see, e.g., Garrett and Rodden 2003). This increase has political and sociological explanations. It has many possible consequences as well, some of which are considered to be beneficial. One of these—indeed, a critical one—is that federal institutions improve the representation of the public in government. There are good reasons to believe that federalism does enhance representation, to be sure. But there also are reasons to believe that it attenuates the relationship between public opinion and policy. Effective policy representation presupposes public responsiveness to policy itself; that is, it presupposes that the public effectively notices what policymakers actually do. There are two reasons. First, public responsiveness provides an important motivation for politicians to represent public preferences: a monitoring public. Second, public responsiveness makes public inputs into the policy process meaningful for policymakers: it allows for informed public preferences. Representative democracy thus depends on public responsiveness to policy. The stronger the public responsiveness, the greater the basis for representation. By corollary, weaker public responsiveness will tend to weaken representative democracy.1 It is through this lens that the current article addresses federalism
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".