DNA Testing for Family Reunification in Canada: Points to Consider
Bibliographic record
Abstract
Countries have adopted different laws, policies, and practices that allow immigration officers to request in certain cases DNA tests to confirm biological relationships in the context of family reunification. In Canada, Citizenship and Immigration Canada has adopted a policy of suggesting DNA testing only as a last resort in cases where no documentary evidence has been submitted or where the evidence provided is deemed unsatisfactory. However, in practice, there have been concerns on the increasing use of DNA tests in family reunification processes of nationals from certain regions including Africa, Asia, and Latin America. Moreover, the Immigration and Refugee Protection Regulations (IRPR) presents a biological definition of family as a determinant of parenthood in the context of family reunification that is inconsistent with the psychosocial definition used in provincial family laws. Although there are cases that can justify the request for DNA tests, there are also significant social, legal, and ethical issues, including discrimination and unfair practices, raised by this increasing use of genetic information in immigration. This policy brief identifies points to consider for policymakers regarding the use of DNA testing in Canadian family reunification procedures. These include (1) the need to refine the policy of “using DNA testing as a last resort” and its implementation, (2) the need to modify the definition of “dependent child” under the IRPR to reflect the intrinsic reality of psychosocial family ties, and (3) the importance of conducting more research on the use of DNA testing in other immigration contexts.
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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 | 0.025 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".