Editorial Canada, Chrysotile, and the Search for Truth
Bibliographic record
Abstract
I had hoped that this issue would include a commen-tary on the health risks from chrysotile asbestos and the degree to which there is a consensus on this sub-ject. The commentary has been written, submitted and peer reviewed, but cannot be published because it draws on a report which the Canadian government has had since mid-March, but has not published. This is an annoying piece of needless government secrecy, but it has wider interest as an example of the use of science in policy. Canada’s attitude to chrysotile is controversial be-cause of its continuing production and promotion of the substance, preferring controlled use in a world where many countries have banned all asbestos. In 2006, Canada produced 175 000 tonnes, which it exported to 70 countries (Natural Resources Canada, 2007). It is by no means the largest producer—2006 production estimates included 1 120 000 tonnes by
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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.021 | 0.023 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".