Mapping the Links: Citizen Involvement in Policy Processes By
Bibliographic record
Abstract
When CPRN asked a representative sample of Canadian citizens what matters for their quality of life, they named nine different policy domains, from health care to safe communities.1 The domain that was at the top of the priority list was their political rights. Why, then, do so many studies also find that citizens are ambivalent, some would say apathetic, about their possibilities for being involved in the parliamentary system and in decisions that affect their lives? There is a growing literature and much debate about the need to reform Canada’s political institutions. It is, of course, important to ensure that legislatures are representative, that elections are fair and efficient, and that political parties play their roles effectively. Enhancing the legitimacy of these institutions would undoubtedly encourage more citizens to exercise their vote and to participate in the political process. But there is another dimension to the question – that is, whether and how today’s citizens, who are much more educated and independent minded than earlier generations, could be more directly involved in the policy process, as individuals and as members of civil society organizations. Exploring and promoting new forms of citizen involvement occupies everyone from public servants and Members of Parliament to advocacy and community groups and
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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 | 0.027 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.012 | 0.017 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".