CAREX Canada: perspectives on the use of population-based exposure surveillance programs for use in risk or burden estimates: abstract
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective CAREX Canada is a longstanding program of research that develops and disseminates estimates of the number of workers exposed to carcinogens. The objective of this talk is to offer a Canadian perspective on using population-level exposure estimates, with particular consideration of how these estimates have been used in Canadian risk and burden studies, and some of the benefits and limitations of these approaches. Material and Methods CAREX Canada began as a pilot program in 2003, based on methods developed in EU-based CAREX programs in the early 1990s. In 2008, it was supported by the cancer research arm of the Canadian government as a national program of research, who continue to fund it to this day. Using a mixed methods approach including key informant interviews, exposure measurement databases, and expert opinion, along with detailed census information, estimates have been generated for 2006 and 2016, with estimates for 2021 due to be released this fiscal year. Results Estimates of occupational exposure have been generated for >50 agents, many of which also have estimates of exposure level. They have contributed to many policy impacts, including a federal ban on asbestos in 2018 and a shifting of provincial approaches to reduce outdoor workers’ sun exposure. They have also been used in the national Burden of Occupational Cancer study for Canada, in addition to a number of epidemiological studies where CAREX estimates were converted into job exposure matrices. Conclusion CAREX Canada estimates have been used for policy influence and change, to raise awareness of occupational cancer for workers, their employers, and society more broadly, and have been translated into job exposure matrices for use in epidemiological investigators. While data like these are extremely important for understanding the extent of occupational cancer and disease, it is important to consider the limitations of these approaches. Abstract from: 30th Epidemiology in Occupational Health Conference (EPICOH 2025), Hosted by Institute for Risk Assessment Sciences, Utrecht University, 6–9 OCTOBER 2025, Utrecht, the Netherlands
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it