The Contested Access of Visible Minorities to Public Parks in Toronto: Analysis of the Determinants of Accessibility
Bibliographic record
Abstract
Access and the distributional equity of public parks have significant impact on health. Accessing a park is not only about how people are physically able to reach it but whether and how they are able to secure the mental and physical benefits to health and well-being that are known to be associated with park and greenspace access. This may be in part determined by whether one feels a sense of inclusion, comfort, or welcoming through the design and other attributes of the park itself. Thus, there are numerous visible and invisible variables that can either hinder or support visible minorities’ access to healthy-built environments, in this case, namely parks. In this context, visible minorities can view access to parks from different perspectives that go beyond the existing spatial measurement tools. This study aimed at grounding spatial segmentation database and statistical models that can inform our knowledge on how visible minorities interact with parks in Toronto. The study applied the General Linear Model of Factor Analysis and the grouping of the Principal Component Analysis (PCA) to predict the population variables loading with the Physical Activity Index-, which is proved to be directly proportional to a level of access to parks. Second, based on the new set of variables, a K-means tool was used to assign Census Tracts (CTs) to seven optimized-segments to capture accessibility differences per immigrants’ social and economic segmentation. This segmentation demonstrated that around 93% of Toronto’s visible minorities live in areas that have low level of access to public parks, 6% live in areas that have moderate access, and less than 1% live in areas with high access, based on the Physical Activity Index-Active. Regarding the environment variables, the research paper designed a weighted model for parks’ attributes that showed that it is difficult to interpret results without putting them into segments. When results were assessed through segments, only number of parks per segments was directly related to access to parks, based on the Physical Activity Index- Active as well.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".