Combining Familial Searching and Abandoned DNA: Potential Privacy Outcomes and the Future of Canada’s National DNA Data Bank
Bibliographic record
Abstract
This article aims to respond to the government’s request by explaining the nature of that relationship and by arguing that the combined use of familial searching and analysis of abandoned DNA would present a serious risk for genetic privacy. The risk is particularly acute given that it would effectively circumvent the existing justification for the NDDB, leading to inclusion of individuals whose DNA profiles have not been uploaded directly onto the data bank. To substantiate this main argument, this article proceeds in three parts. The first describes the current Canadian law on familial searching and the ongoing interest in amending the DNA Identification Act to allow use of this technique on NDDB data. The second part explains the current Canadian law on police use of abandoned DNA, which has largely been shaped by section 8 claims in a series of post-Charter cases. The third part explains how police might depend on the current law allowing broad police use of abandoned DNA to facilitate follow-up on leads derived from familial searching of NDDB information. The possibility presents a major policy consideration that must be acknowledged within the discussion of whether and to what extent familial searching of the NDDB should be authorized in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.059 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.035 | 0.028 |
| Scholarly communication | 0.024 | 0.009 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".