Bibliographic record
Abstract
As scientists and science educators challenge the epistemological hegemony and cultural imperial-ism of Western modern science by insisting that definitions of science be expanded to include other scientific traditions including traditional ecological knowledge (Berkes 1988, 1993; Inglis, 1999; Warren 1997; Williams & Baines 1993; Snively & Corsigila 2000), we have not seen much of a coe-taneous movement in civil and natural resource engineering. The decolonization of Canadian cities must begin with the acknowledgement of the role engineering, architecture and urban planning has had in the perpetuation of colonialism. This paper works to identify directions for the decoloniza-tion of infrastructural systems through a reconsideration of pre-contact Indigenous architectural and infrastructural histories, a recognition of the ways in which infrastructure was often used as an instrument of colonial land claims, and the various ways in which Indigenous peoples, communities, and knowledges have contributed to the infrastructures that populate our contemporary geography. It is through an acknowledgment of infrastructure as actant in colonialism and the contributions Indigenous peoples and knowledges have had in the development and implementation of our infrastructural systems that we can begin to expand and deepen our understanding of the relationings between knowledge, infrastructure, ecosystems and Indigenous peoples. Finally, this paper considers the ways in which Indigenous design principles offer a great deal of potential in the creation of more environmentally and socially sustainable communities, and even regenerative design.
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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.059 |
| Scholarly communication | 0.015 | 0.034 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.007 | 0.019 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".