Stimulating a Canadian narrative for climate
Bibliographic record
Abstract
This perspective documents current thinking around climate actions in Canada by synthesizing scholarly proposals made by Sustainable Canada Dialogues (SCD), an informal network of scholars from all 10 provinces, and by reviewing responses from civil society representatives to the scholars’ proposals. Motivated by Canada’s recent history of repeatedly missing its emissions reduction targets and failing to produce a coherent plan to address climate change, SCD mobilized more than 60 scholars to identify possible pathways towards a low-carbon economy and sustainable society and invited civil society to comment on the proposed solutions. This perspective illustrates a range of Canadian ideas coming from many sectors of society and a wealth of existing inspiring initiatives. Solutions discussed include climate change governance, low-carbon transition, energy production, and consumption. This process of knowledge synthesis/creation is novel and important because it provides a working model for making connections across academic fields as well as between academia and civil society. The process produces a holistic set of insights and recommendations for climate change actions and a unique model of engagement. The different voices reported here enrich the scope of possible solutions, showing that Canada is brimming with ideas, possibilities, and the will to act.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.054 | 0.023 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".