“Cancer in the family” and genetic testing: implications for life insurance
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
The potential for discrimination when applying for insurance can be of concern for individuals with a family history of cancer or of a genetic disorder and who are considering genetic counselling or genetic testing. The actual incidence of "genetic discrimination", however, is not known, despite considerable media coverage of this issue. The clinical details required by insurers have received less attention. We obtained primary application and personal statement forms used by 21 different underwriters of voluntary life insurance and found substantial differences in the information requested about family history and genetic testing. All insurance applications, however, contained a duty of disclosure that would require revealing the result, if known by the applicant, of a genetic test in a family member. Therefore, decisions made by family members can affect insurance applications, and people considering genetic testing may also need to consider the implications of the results for other family members. Health practitioners should balance the potential benefits of appropriate genetic testing against potential restriction to life and income-protection insurance when advising people about genetic testing.
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 | 0.001 | 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 it