The Provision and Accessibility to Parks in Ho Chi Minh City: Disparities along the Urban Core—Periphery Axis
Bibliographic record
Abstract
In Ho Chi Minh City (HCMC, Vietnam), there is now an urgent need for evaluating access to parks in an effort to ensure better planning within the context of rapid and increasingly privatized urbanization. In this article, we analyze the provision and accessibility to parks in HCMC. To achieve this, the information gathered was then integrated into the geographical information systems (GISs). Based on an Ascending Hierarchical Classification, we were able to identify five different types ranging in their intrinsic characteristics. The accessibility measurements calculated in the GISs show that communities are located an average of at least 879 meters away from parks, which is a relatively short distance. Children have a level of accessibility comparable to that of the overall population. Accessibility also seems to vary greatly throughout the City—populations residing in central districts (planned before 1996) enjoy better accessibility compared to those in peripheral neighborhoods (planned after 1996). Parks located in areas planned between 1996 and 2002 are the least accessible, followed by parks in areas planned after 2003. Our findings suggest possible approaches that could be used to help ensure the quality of parks and their spatial accessibility.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".