Limits to growth and quality of life in Oxnard, California: an evolving set of indicators of a city's sustainability reflecting the SOAR ordinances
Bibliographic record
Abstract
This report was prepared by the faculty and students from the California State University at Northridge Urban Studies & Planning Program and Department of Health Sciences with assistance and guidance from the Sustainability Council of Ventura County. A summary of this report was subsequently prepared by the Sustainability Council. The study was funded by a "Partnership Grant" from the California Urban and Environmental Resource Education Center. \nReaders will undoubtedly find some indicators more relevant than others. This is natural given different people's perspective. However, it is equally true that some indicators are simply superior to others as measuring instruments. Therefore, one should take away from this study an appreciation for what makes a good indicator as well as what short-comings should be avoided when developing indicators. It is hoped that readers can apply such lessons as they undertake the development of sustainability indicators in their own communities and as the indicators for the City of Oxnard are tracked into the future.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".