Communicative regionalism and metropolitan growth management outcomes : a case study of three employment nodes in Burnaby --an inner suburb of Greater Vancouver
Bibliographic record
Abstract
In North America, metropolitan growth management (MGM) has been significantly influenced by communicative regionalism. The latter is rooted in communicative planning theory, stressing dialogue and consensus in problem-solving. To explore the impact of communicative regionalism on actual growth management outcomes, this dissertation investigates a case study on the implementation of communicatively-informed regional plans in metropolitan or Greater Vancouver, Canada, as they have impacted three employment nodes in suburban Burnaby. The dissertation applied a three-part methodology, involving the collection of empirical outcome data, analysis of plan development against communicative planning criteria, and the critical application of an Actor Network Theory (ANT) lens to better examine relationships and interactions of key government agencies during MGM plan development and implementation. The analysis suggested mixed results for goal outcomes. Notably, it found that longstanding goals for attracting office employment to a designated Regional Town Centre were not achieved to the desired degree. In explaining results, the analysis supplied empirical evidence of recent critiques of communicative planning theory. Such results appear to support calls by other theorists for the development of a post-communicative approach to theory and practice. The dissertation recommends five areas of more concerted research in this regard. First, researchers interested in planning processes would be wise to make more in-depth explorations of the link between power and action. Second, the presence and degree of instability in any given network of actors participating in growth management can create constraints or opportunities for this process. The role of instability must be better reflected and appreciated in communicative and/or post-communicative regionalism. Third, there must be greater recognition of differentiated stakeholder consultation needs, and place-specific receptivities to consultation short cuts. Fourth, more detailed work is needed to develop best practices for the information-sharing aspects of growth management. Finally, there is value in examining further the roles and skills of various individuals playing a translation role (i.e., bridging interests between different stakeholders or groups). This translation role occurs in growth strategy development and other planning exercises, as a means of enabling both better information exchange and of facilitating the ongoing stakeholder involvement throughout the plan implementation phase.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".