A Guide to Climate Change for SMEsi
Bibliographic record
Abstract
Canadian Chamber of Commerce has been the largest, most influential advocate for business in Canada. Founded with the aim of creating a strong, unified voice for Canadian business and a set of values from which policies encouraging prosperity would emerge, the Canadian Chamber of Commerce continues to be the only voluntary, non-political association that has an organized grassroots affiliate in every federal riding. Mission: As the national leader in public policy advocacy on business issues, the Canadian Chamber of Commerce’s mission is to foster a strong, competitive, and profitable economic environment that benefits not only business, but all Canadians. How we achieve this? Through a two-way consultative process with our membership, the Canadian Chamber of Commerce steers the debate on federal and international policies affecting business. In collaboration with our members, the Canadian Chamber of Commerce acts on policy resolutions, researching and developing strategies on a “best practices ” basis for business. It then communicates these viewpoints to officials in Ottawa and internationally, to the Canadian public, and to the media. Why is the Canadian Chamber of Commerce effective? The Canadian Chamber of Commerce is the leading organization to bring together all types of Canadian business. It speaks for all business — from the smallest to the largest company — in every sector and in every corner of the country. The Canadian Chamber
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.097 | 0.065 |
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".