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 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 | 0.064 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.025 | 0.013 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".