Who really governs Vancouver? Community power and regime theory revisited
Bibliographic record
Abstract
The central research question herein is “how do coalitions of government and non-government actors get created and influence the decision-making processes of municipal government in Vancouver, British Columbia?” The goal of this effort is to better understand “who really governs?” (Dahl, 1961) at the municipal level of government in the city during two ‘adjacent’ eras – the development of the post-Expo ’86 lands in the late 1980’s and early 1990’s, and the creation and implementation of the Vancouver Agreement (VA), including the development of Vancouver as North America’s first supervised/safe injection site/harm reduction model, in the late 1990’s and early 2000’s. This dissertation considers not only the structures, actors and ideas of municipal governments but also the creation, influence and power of the various coalitions, the urban regimes, as defined by Stone (1989), that form around local decision-making. It is clear from this examination that coalitions of government and non-government actors, urban regimes, were created and influenced the decision-making processes involved in the development of former Expo ’86 lands and the creation and implementation of the Vancouver Agreement. In addition, there were continuities and discontinuities identified, linked to the type of policy being considered by the Vancouver municipal government. In sum, this analysis found that the nature of the decision-making processes, and by extension the urban regimes that were created, were issue-dependent. Urban regimes involved in what Bish and Clemens (2008) have described as “hard” (or “engineering”) issues, such as land development, were substantially different in nature to those involved in “soft” (or human policy”) issues, such as the provision of addiction services - the substance of policy issues mattered more than institutions.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.055 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".