Lessons from Canada for green procurement strategy design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We derive lessons for green public procurement (GPP) by examining it in the context of Canadian federal government expenditures in several sectors. These show that successful GPP is neither simple nor automatic but requires alignment of green policy visions between payers, purchasers and producers, and the existence of appropriate procurement frameworks to allow this alignment to persist. Attaining and maintaining this alignment longitudinally is especially difficult as priorities, and governments can change over time, ‘de-aligning’ any initial agreement on the merits of the strategy behind ‘strategic procurement’ of any kind. While less acute for short-term procurement, this problem exists for many longer-term green procurement projects and can lead to government attempts to downplay long-term efforts and seek less complex short-term purchases where alignment is easier to establish and maintain but where green efforts may be less impactful. These dynamics are illustrated in the case of green procurement efforts made in Canadian federal programmes including the little-examined but important defence sector.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 it