Multistakeholder roundtables: civil society, social capital and conflict management
Bibliographic record
Abstract
In the last four decades, demands for greater citizen participation in government decision-making have changed the face of governance in Canada. One of many innovations that have been introduced is stakeholder roundtables that operate on the basis of consensus and act in an advisory capacity to government on policy and planning issues. This MDP focuses on the application of multistakeholder roundtables in the domain of land-use planning in non-urban areas, with a particular focus on Crown land planning. This is a vital area of concern as Canada's expansive Crown lands are the locus of competing interests. Roundtables are expected to produce some beneficial outcomes, addressing some of the weaknesses of traditional top-down planning and resource management practices. I have chosen to focus on three outcome criteria, which are in essence social goals: strengthening civil society; building social capital; and effectively managing conflict. A literature review of case studies, best practices, and evaluation was conducted, in order to discover facilitators and barriers to achieving the goals of roundtable processes, particularly in relation to civil society, social capital and conflict management. One such process conducted by the Ontario government, Lands for Life, is used as an illustration. Discussion and recommendations are provided regarding eleven process design factors selected for their strong relation to the three social goals. It is noted that outcome goals of roundtables can be internally inconsistent or contradictory, so that, for example, a design choice that increases social capital may undermine conflict management. These tensions are discussed as part of the final chapter.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".