SAME SEX, DIFFERENT RIGHTS: AMENDING U.S. IMMIGRATION LAW TO RECOGNIZE SAME‐SEX PARTNERS OF REFUGEES AND ASYLEES
Bibliographic record
Abstract
Overcoming a long history of anti‐gay sentiment preserved in federal immigration law, the United States has made admirable advances during the past two decades in the protection it affords gay immigrants. Despite this promising progress, and in contrast to the practices of all other industrialized democracies, the United States remains firm in its refusal to federally recognize any form of same‐sex partnership, a decision which bears directly on those relationships considered valid for immigration purposes. The Uniting American Families Act (UAFA) represents the closest any proposed legislation has come to successfully granting immigration rights to gay immigrants. However, through its restrictive provisions, the UAFA fails to fully account for the needs of refugees, asylees, and their same‐sex partners. This Note argues that, while the UAFA is a step in the right direction, it does not go far enough to protect gay refugees and asylees. It further proposes that legislation be enacted which provides this unique segment of the immigrant population the opportunity to share their lives together, free from fear of persecution. It advocates for the use of the conjugal partner provision set out in Canada's Immigration and Refugee Protection Act as a template for changes to U.S. immigration law, thereby expanding the category of relationships viewed as valid for the purpose of immigration.
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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 | 0.033 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.021 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".