CSA Z1007: A new management standard from the Canadian Standards Association for the management of hearing loss prevention programs
Bibliographic record
Abstract
Canada has a fragmented set of norms for Hearing Conservation owing the 14 jurisdictions that set standards for these programs. CSA Z1007, a new standard written with the support of Canadian regulators , seeks to establish norms, which can be used to manage these programs as hearing loss prevention programs. The difference between loss prevention and conservation is a proactive stance seeking to remove the causes of noise induced hearing loss before permanent hearing damage takes place. The standard covers all aspects of hearing loss prevention from detection of potential toxic noise through to proactive measures to determine if the program is being effective. The standard is compatible with and reflective of CSA’s other standards in this area. The presentation will address the fragmented nature hearing loss prevention in Canada, how the standard seeks to address that, what proactive measures can be taken, and how to determine if the standard is being applied effectively. As well, there are several informative annexes addressing parts of the program in greater detail and Best Practices for those who wish to excel in this area. The standard was published in March of 2016, and is currently seeking adoption from the regulators that enabled its creation.
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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 | 0.025 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".