Bibliographic record
Abstract
In their article ‘Marginally scientific? Genetic testing of children and adolescents for lifestyle and health promotion’, Caulfield et al. provide readers with a thoughtful and well-researched introduction to many of the ethical, legal, and social issues (ELSIs) raised by direct-to-consumer genetic testing ofminors for reasons unrelated to disease. In their concluding section, the authors question whether the ELSIs discussed are ‘significant enough to trigger a regulatory response’ given the ‘lack of evidence of direct harm’.Their analysis of several potential lines of action represents an important followup to the many concerns discussed earlier in the paper. While the article doesmention the role of ‘educational interventions’ and ‘providing accurate information to parents’, this option remains fairly underdeveloped in comparison to the article’s focus on regulatorymeasures. However, it remains unclear whether the ELSIs discussed represent a threat unique enough to merit specific new policy amendments. As Caulfield points out in a previous article, ‘The fact that most genetic risk information is not tremendously predictive and that people are not, in general, having unique adverse reactions to the genetic results are, at a minimum, justifications for being cautious about any exceptionalist approach to the regulation of genetics.’1 Given this level of uncertainty, we suggest that this discussion should be complemented by a more detailed look at the role science communication could play in helping the general public gain a better understanding of the potential and the shortcomings of these technologies. One justification for this viewpoint lies in the very magnitude of the concerns being discussed. The genetic testing industry has been growing rapidly,2 both in market size
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 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 | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".