Building Canadas Low Carbon Future: Opportunities for the Philanthropic Sector
Bibliographic record
Abstract
The philanthropic sector has a key role to play in accelerating Canada's transition to a low carbon future. This report provides an overview of the major gaps and opportunities for action across all sectors of Canada's economy, as well as cross-cutting measures to enable systemic change. It concludes with recommendations on the path forward for the philanthropic sector, and with a series of blue-sky ideas from interviewees that could unlock transformational change.The landscape has evolved significantly since 2015, when we last advised on philanthropic opportunities to address climate change. Yet despite major progress, emissions continue to rise and climate change remains a highly polarized issue in Canada. The COVID-19 pandemic, which began in earnest in the midst of this review, presents a new set of challenges, along with an historic opportunity to 'build back better.'
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".