Designing the Urban Coexistence
Bibliographic record
Abstract
This paper critically examines the prevailing paradigms of environmental and spatial justice, emphasising the existing disparities in policies that predominantly favour human interests while overlooking the fundamental rights and well-being of non-human species. Despite the growing acknowledgement of the importance of establishing a deeper connection between human and non-human actors for overall well-being, a pervasive speciesism mindset persists, distancing humans from the broader natural world. This separation from nature profoundly influences the formulation of policies and justice, establishing a bias that focuses primarily on human concerns and environmental conditions tailored to human well-being. Architects and planners, despite possessing the potential to enrich habitats for various species, frequently adopt human-centric approaches that marginalise other-than-human entities, restricting their access to the immediate surroundings of human territories and impeding opportunities for immersive nature experiences. This article advocates for a comprehensive paradigm shift in architectural practices, urging a more inclusive and equitable approach that extends spatial and environmental justice to encompass the diverse needs and rights of both human and non-human species within the urban landscape. The conclusions underscore the urgent need for architects and planners to re-evaluate their approaches, fostering an environment that supports coexistence and acknowledges the interconnectedness of all species. In the face of global biodiversity concerns and international frameworks such as the Kunming-Montreal Global Biodiversity Framework, the research contributes to the discourse on sustainable and ethical design practices, advocating for a future where spatial and environmental justice extends its reach beyond the confines of human experience to create a respectful and just coexistence with the entire ecological community.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".