Assessing the Degree of Sustainability Integration in Canadian Public Sector Procurement
Bibliographic record
Abstract
The purpose of this study was to identify the current state of sustainability integration into Canadian government procurement and make recommendations on how to deepen current integration in order to accelerate the advancement of existing sustainability goals. We reviewed 50 publicly available Requests for Proposals (RFPs) issued between 2016 and 2019 and evaluated the significance of sustainability integration and the expanse of considerations using two measurement schemes. Our analysis suggests that sustainability integration into RFPs is currently superficial with limited integration into the evaluation process. We also found that the integration of sustainability was narrow with significant gaps in the breadth of environmental and social impact areas that were considered. As such, we provide insights and recommendations that will enable governments to accelerate the advancement of sustainability through the use of procurement.
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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 | 0.035 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.031 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| 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".