Evidence from the Study of the Social Dynamics of Economic Performance
Bibliographic record
Abstract
We contribute to a revised politics of class in urban development by draw-ing on recent theoretical work on class tensions and inequalities as a barrier to more egalitarian and sustainable economic development. We provide evi-dence from an empirical study of the social dynamics of economic perfor-mance in the city of Kingston, Ontario, to argue that class politics is a key dimension of social dynamics in this unusually segmented and spatially segre-gated Canadian city. Our findings suggest that poor economic performance can be understood through a class lens in two ways. First, “creative class” economic development strategies and growth machine politics perpetuate economic stagnancy because they fail to confront underlying class inequali-ties. Second, the absence of collaborative and socially inclusive leadership—a contributor to poor economic performance—emerges when local institu-tional leaders fail to find common ground over social problems. We con-clude with questions about how policymakers can alleviate class divides for better economic performance as well as contribute to the new debates in the literature on class and urban development. at PENNSYLVANIA STATE UNIV on May 12, 2016uar.sagepub.comDownloaded from
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".