The Multiple Deindustrializations of Canada’s Maritime Provinces and the Evaluation of Heritage-Related Urban Regeneration11 For valuable comments on an earlier version of this essay, the authors wish to thank Donald J. Savoie and the participants at the Swansea Conference organized by the Canadian Studies in Wales Group on Regeneration, Heritage and Cultural Identity: Trans-Atlantic Perspectives, June 2013.
Bibliographic record
Abstract
The Maritime provinces of Canada share with many other nations the experience of nineteenth-century industrialization and twentieth-century deindustrialization. For deindustrialized areas, the social and environmental pressures imposed by deindustrialization are frequently held to be open to mitigation through urban regeneration projects that seek to build on existing cultural heritage and ultimately enable communities to thrive in both cultural and economic terms. In the Maritime provinces, however, two factors have greatly complicated the emergence of effective urban regeneration. One is the historical complexity of both industrialization and deindustrialization in the region, while the other is the critical weakness of evaluation criteria for defining success in urban regeneration and thus assessing the effectiveness of regeneration projects. Without advocating the adoption of a ‘one-size-fits-all’ model, and recognizing the complexity – even intractability – of the ‘wicked problems’ that attend any regeneration project, this essay will argue that historical and policy-related analysis can be combined to generate a regional approach to urban regeneration and its evaluation, which will take account of the need to maintain existing cultural integrity and to support processes of policy learning and social learning.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| 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".