ENGINEERING, PATRIARCHY, AND THE PLURIVERSE: WHAT WORLD OF MANY WORLDS DO WE DESIGN? WHAT WORLDS DO WE TEACH?
Bibliographic record
Abstract
This paper presents a brief review of sustainability definitions and analyzes ways of designingtaught in our Engineering education system, specifically acknowledging the capitalist, patriarchal, colonial, Western world that much, if not most, of current Engineering practice situates itself within. Included in these frameworks are pluriversal design, co-design, participatory design, and discursive design. Another important topic that will be examined is the dualist perspective embodied in Engineering practice that creates a distinction between “man” and “nature”. While this problem is inherently systemic, our intention is to provide a partial record of our own critical selfreflection,contextualized using critical theory. It is intended as a starting place for settler-descendent NorthAmerican educators to begin to contextualize our own approaches, not as a way for us to guide steps forward, but instead to begin a self-critique of current approaches that need continued work.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".