Ethical, Legal, and Social Issues in Health Technology Assessment for Prenatal/Preconceptional and Newborn Screening: A Workshop Report
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
Prenatal/preconceptional and newborn screening programs have been a focus of recent policy debates that have included attention to ethical, legal, and social issues (ELSIs). In parallel, there has been an ongoing discussion about whether and how ELSIs may be addressed in health technology assessment (HTA). We conducted a knowledge synthesis study to explore both guidance and current practice regarding the consideration of ELSIs in HTA for prenatal/preconceptional and newborn screening. As the concluding activity for this project, we held a Canadian workshop to discuss the issues with a diverse group of stakeholders. Based on key workshop themes integrated with our study results, we suggest that population-based genetic screening programs may present particular types of ELSIs and that a public health ethics perspective is potentially highly relevant when considering them. We also suggest that approaches to addressing ELSIs in HTA for prenatal/preconceptional and newborn screening may need to be flexible enough to respond to diversity in HTA organizations, cultural values, stakeholder communities, and contextual factors. Finally, we highlight a need for transparency in the way that HTA producers move from evidence to conclusions and the ways in which screening policy decisions are made.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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