Sustainability and the urban landscape: introduction of a qualitative assessment tool for understanding and enhancing sustainability in urban open space
Bibliographic record
Abstract
This project introduces a way of operationalizing the idea of sustainability by applying its principles to open space in the urban landscape. Landscape is defined as the land surface, composed of a mosaic of ecosystems and land uses, that provides the setting for human activities. The rationale for the project is that people are deeply influenced by and keenly interested in landscape features, so landscape can serve as a medium for learning about sustainability because our ways of using land form part of the broader picture of our relationship with the earth. The landscape of urban areas deserves attention because urban dwellers experience it daily and sometimes exclusively, and because of the global trend toward urbanization of natural landscapes. Sustainability is conceptualized as a system characteristic that arises from three other necessary conditions within the system: provision for ecological viability, provision of adequate human life quality and consideration of equity. A landscape ecological model of sustainability was operationalized by linking its variables to urban open space features via indicators constructed from literature sources and based on visual assessment of observable landscape conditions. Use of this landscape assessment tool (set of indicators) was demonstrated by assessing several test sites in an urban district. The tool's usability was partially examined through trials with potential users. Three broad conclusions are drawn from the project. First, findings from the test sites indicate that amenity functions in the urban landscape are only moderate and ecological functions are unexpectedly high despite management for amenity. This suggests that urban ecosystems could flourish and serve as repositories of ecological function if they were enhanced by planning and management. Secondly, the urban open space assessment tool shows potential for usefully operationalizing sustainability theory, though more testing of its educational value and accuracy is needed. Finally, the sustainability model used in the project shows that sustainability requires the achievement of human well-being through the satisfaction of social needs as well as material sufficiency and ecological integrity. Satisfaction of these different needs can be complementary and can be achieved within systems of human activity such as urban open space use.
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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 | 0.002 | 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".