Advancing Climate Action Through Scope 3 Emissions Evaluation and Reporting for the University of Calgary
Bibliographic record
Abstract
This study establishes a Scope 3 greenhouse gas (GHG) emissions baseline for the University of Calgary in 2023–2024 to support the institution in beginning comprehensive reporting. Using the GHG Protocol as a guide, the assessment focused on material categories including purchased goods and services, capital goods, business travel, commuting, fuel- and energy-related activities, and waste, with comparisons to the 2011–2012 baseline. A hybrid approach using procurement records, Environmentally Extended Input-Output factors, manufacturer life cycle data, travel surveys, and waste audits was applied. Results indicate that procurement and commuting are the largest contributors, while waste and upstream energy activities are smaller but still material. The analysis faced significant data limitations across nearly all categories, highlighting the need for improved data systems. Findings provide both a baseline and a roadmap to help the University of Calgary advance Scope 3 reporting and climate action.
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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 | 0.050 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".