Crafting a Sustainable Engineering Vision Through a Consultation Process
Bibliographic record
Abstract
A wide-ranging consultation process was conducted by Polytechnique Montréal between 2022 and 2023 explores the impact of environmental, technological and societal transformation on the work of engineers and competencies needed, as well as on engineering education. This study highlights a mobilization approach aimed at co-creating a competency profile of the engineer of tomorrow. The methodology includes interviews, internal and external surveys, and a forum bringing together over 250 stakeholders in May 2023. The results provide a better understanding of the global, national and local issues engineers are facing, as well as the competencies required to support the engineer's global development from a sustainable engineering perspective. This vision captures the essence of the engineer's future role, focusing on collaborative efforts to define and implement an updated engineer profile, integrate it into educational pathways, and streamline accreditation processes. This vision aligns with a transformative epistemology and UNESCO's sustainable development goals, offering a blueprint for institutions to mobilize their ecosystem towards common goals.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".