CHEM ENG 3S03: FUNDAMENTAL AND SYSTEMIC APPROACH TO SUSTAINABLE CHEMICAL ENGINEERING
Bibliographic record
Abstract
Examination of the current Chemical Engineering curriculum at McMaster University reveals areas that can be adapted to teach sustainability tool and concepts without removing technical and fundamental knowledge. Creation of a conceptual sustainability-driven course entitled, CHEM ENG 3S03 – Fundamental and Systemic Approach to Sustainable Chemical Engineering addresses many of these concepts as a stand-alone technical elective option. The course is separated into ten modules that concurrently exist as individual courses within the Chemical Engineering department, with adapted reading material and systemic approaches to sustainability. It is proposed that a pedagogical strategy should be adopted to produce sustainabilityspecific learning outcomes. Metrics from the design of CHEM ENG 3S03 can be utilized to modify other Engineering courses to meet the needs of accreditation and integrate sustainability into Engineering education at McMaster.The concept of integrating sustainability into the Chemical Engineering curriculum is inspired by work completed by the Taskforce for Sustainability in Engineering Education. The Taskforce is a product of McMaster University’s Dean of Engineering, David Wilkinson, and the Strategic Plan 2009-2014. Within the report, it is an objective of the McMaster University Engineering Faculty “to examine the global engineering concept and determine how it can be best integrated into the undergraduate curriculum.” Aligning with this goal, the taskforce completed significant work in curriculum mapping and setting of sustainability attributes for undergraduates. The work of this taskforce led to the ideology of course development within each Engineering discipline with an emphasis on graduating Engineers that are proficient in competencies and hold specific desirable attributes.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".