Indigenizing Engineering education in Canada: critically considered
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article critically considers the work being done to bring Indigenous Peoples, Knowledges, and perspectives into the dominant structures of engineering education in Canada. We use Gaudry and Lorenz’s (2018. “Indigenization as Inclusion, Reconciliation, and Decolonization: Navigating the Different Visions for Indigenizing the Canadian Academy.” AlterNative: An International Journal of Indigenous PeoplesAlterNative 14 (3): 218–227. doi:10.1177/1177180118785382) spectrum of Indigenization to evaluate self-reported contributions from 25 engineering programs and four engineering organizations. Findings show much of the work being done in Canada is in Indigenous Inclusion and Reconciliation Indigenization, with some Decolonial Indigenization. Efforts in reconciliation and decolonization are seen predominantly in integrated, grassroots initiatives, with institutional initiatives found largely in inclusion. We submit that a diversified strategy and decolonized policies are needed to achieve Decolonial Indigenization. The intention of this work is to create an ethical space where Indigenous and non-Indigenous engineering educators can listen to and learn from one another. Guided by Etuaptmumk (Two-Eyed Seeing), we can advance Indigenous ways of knowing, being, and doing in engineering education in Canada and around the world.
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.
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 | 0.001 | 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 | 0.001 | 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 it