Genetic information and insurance : a contextual analysis of legal and regulatory means of promoting just distributions
Bibliographic record
Abstract
This thesis analyzes the rationale, appropriateness and value of the available legal and regulatory means to deal with genetic discrimination in the context of insurance. Insurance is used as a paradigm case for discussing the legal means to address the concerns related to the impact of new medical technologies. A new framework is proposed for evaluating the potential impact of such new technologies on people's ability to participate fully in social life and to have access to important social goods without unfair discrimination based on certain inherited traits. A "thick" contextual method is used, which involves a detailed description of the medical, social, and legal context of the debate. The approach is based on Michael Walzer's theory of justice, which posits that in assessing the fairness of the distribution of a particular good, one must take into account the nature of the good as determined by the specific socio-historical context in which it obtains its shared meaning. Walzer's theory is used in the thesis to critically analyze the regulatory and legislative means introduced in several countries to curb genetic discrimination. It is further argued that Walzer's contextual analysis resembles the approach taken by the Canadian Supreme Court in the context of anti-discrimination law. Canadian human rights law is analyzed in detail to describe how genetic discrimination could be dealt with under the current provisions and how human rights law can be used to create conditions of substantive equality. The thesis concludes with an analysis of various legal and regulatory options to deal with genetic discrimination and its impact on human rights in the Canadian context. The establishment of a regulatory body is proposed, with the mandate to review the appropriateness of the use of new tests in the context of insurance. I argue that this review process, and the contextual analysis that should be involved in this process, would constitute a useful step towards creating conditions for substantive equality, not only for those who are genetically disabled, but for all those who are affected by real or perceived disabling conditions and stigmatizing traits.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".