Ethical Urbanism: Cultivating Compassion to Drive the Development of Sustainable Urban Landscapes
Bibliographic record
Abstract
Addressing anthropogenic climate change requires grand political, economic, and societal reforms but to make meaningful change, it must start with compassion and the realization it is humanity’s ethical duty to do so. By preserving natural features, establishing community, and integrating a sustainable food system, Ethical Urbanism is a new ecological design approach that cultivates compassion for the environment and all living beings to address climate change. Three ecologically-driven case studies were examined to mitigate issues that would arise in the development of an ethical community. These lessons then guided the design exploration of a 338 hectare site in Guelph, Ontario. The redevelopment of Guelph’s York Lands site establishes a mixed-use mid-density eco-community that provides valuable space for both humans and non-humans in an urban setting. Ethical Urbanism, established in this thesis, rejects the commodification of living beings. It strives to exist not to the detriment of others and the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".