Assessment of territorial justice using geographic information systems: A case study of distributional equity of golf courses in Calgary, Canada
Bibliographic record
Abstract
Abstract Minority groups and their residential locations have widely been examined in the environmental justice literature. Few studies, however, have focused specifically on territorial justice and the distributional equity of golf courses. Thus, this study examines the distributional equity of golf courses as they relate to Chinese residents and other disadvantaged groups in Calgary, Canada, over a 10‐year time span (1991 to 2001). Results indicate that Chinese were concentrated in several parts of Calgary over this period of time, and they were more likely than Anglo‐Canadians to reside in census tracts that did not have, or were not near to, golf courses. However, the distributional inequity decreased during more recent years, primarily because of the construction of new golf courses. In addition, no significant difference was found between less affluent and more affluent households, suggesting that ethnicity is the most important factor affecting close proximity to golf courses. Study limitations, implications, and future research recommendations are discussed.
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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 | 0.001 | 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".