Bibliographic record
Abstract
Can Canada build new oil pipelines and reduce its greenhouse gas (GHG) emissions pursuant to its international legal commitment under the Paris climate change agreement? Moreover, can Canada simultaneously promote oil sands production and sustainability? A great many otherwise reasonable Canadians – including academics, NGO and government policy analysts, media pundits, politicians, and members of the general public – insist we can. Paris versus pipelines, on this Panglossian view, is a false choice. This get-rich-and-save-the-environment-too view, however, is fatefully mistaken – the federal government’s own GHG emissions data leave absolutely no doubt about this. But it is mistaken in an interesting and instructive way: Only by excavating and exposing the normative foundations of this view will Canada be able to effectively chart a course towards net zero carbon emissions and sustainability. This article proceeds as follows. Part II examines Canada’s emerging climate change policies through the conceptual prism of Canada as a “carbon democracy.” Parts III and IV use the concept of “carbon democracy” to unpack and explain the contradictions of Canadian climate change policy vis-a-vis climate science and economics, respectively. Part V concludes by sketching out an alternative, democratic pathway for Canadian climate change and sustainability policy.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".