Genetic Discrimination, Life Insurance, and Justice as Fairness
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
In this paper, I use justice as fairness (JAF) to inquire whether any issues of liberal justice are raised by the practice of genetic discrimination in society, in particular from the standpoint of life insurance pricing in Canada. I present three ways in which JAF may apply. First and foremost, Rawls’ negative thesis can be interpreted to say that one’s genetic characteristics are morally arbitrary and therefore persons do not deserve to be advantaged or disadvantaged by the basic structure of society based on these characteristics. Second, as James W. Nickel observes, Rawls’ principle of equal basic liberties can be interpreted to include a right to privacy which is necessary, among other things, in order to protect other basic rights and liberties. Third, as Martin O’Neill maintains, life insurance is a gateway social good that allows individuals to access primary goods and to live a full human life. Therefore, securing this important good on non-discriminatory grounds is of fundamental importance for a society committed to social justice.
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 | 0.000 | 0.002 |
| 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