Producing diversity in a new urbanism community: <i>Policy and practice</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the mid-1990s, Markham in Ontario has embedded new urbanism and smart growth principles in its plans. The policies presume that policies for place diversity – requiring a mix of housing types, uses and densities – will produce social diversity. This article examines planning policies and reviews interview data to understand the challenges in interpreting and implementing a diversity agenda in practice. Although respondents describe Markham as ethnically diverse, census data reveal new kinds of social homogeneity. Planning policies and regulations that call for diversity in housing types, land uses and densities may contribute to place vitality and economic health, but the Markham case suggests that they may not produce social equity. Planners' faith in place diversity as a means to social diversity faces significant challenges in practice.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it