Bibliographic record
Abstract
This paper considers the social, cultural, and structural processes and practices, that are manifested in the built environment and mediated spatially, that create and maintain experiences of exclusion, otherwise known as spatial injustice. Expanding on two decades of case study research and empirical data collected in spatial justice across Canada and Australia, this paper interrogates perspectives of power and spatial injustices that still exist today. These case studies are based in institutions like malls, museums, urban precincts, and universities to usher in a new understanding of universal design through the lens of spatial justice and include creative practice (films), (dis)-audits, co-design processes, and disability allyship. This paper expands on the first comprehensive set of studies across spatial typologies, and how power and spatial justice are manifested and designed into architecture and interior environments-and their fields of knowledge. Key takeaways are new ways of knowing, teaching, and doing in architecture and design to create spatial justice and cultures of inclusion.
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 | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.138 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| 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".