Aviation Safety vs. Medical Confidentiality: Disclosure of Health Information for Accident Prevention and Investigation
Bibliographic record
Abstract
INTRODUCTION: In this article an analysis is made of existing legal provisions and policies regarding medical confidentiality and the use of medical information on pilots, for the reporting of unfit pilots and for accident and incident investigation. An overview is given of the applicable international, European and several national legal frameworks in relation to this question. The applicable national legislation and relating policies of the Netherlands, the U.S., and Canada are compared on this subject. These three States (countries) are selected because of the differences between them in legal provisions when it comes to medical confidentiality of pilots’ health information. The article will conclude with tools derived from this analysis, which can be used to find a balance between medical confidentiality vs. aviation safety.Schuite JM. Aviation safety vs. medical confidentiality: disclosure of health information for accident prevention and investigation. Aerosp Med Hum Perform. 2019; 90(10):872–881.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".