Fleeing Cuba: A Comparative Piece Focused on Toro and the Options Victims of Domestic Violence Have in Seeking Citizenship in the United States and Canada
Bibliographic record
Abstract
The United States Court of Appeals for the Eleventh Circuit decided a case on February 4, 2013 that has undoubted international implications. Toro v. Sec’y dealt with the language of the Cuban Refugee Adjustment Act of 1966 (CAA) and the provisions of the Violence Against Women Act (VAWA). This article focuses on how and why the court reached its decision. It analyzes the conflict between the “plain language” of the CAA and its statutory construction to rebut the court’s assertion that the VAWA self-petition was irrelevant in this case, and ultimately, offer an alternative analysis to this case. This article also explores Canadian immigration law and demonstrates the difference in that nation’s law, as applied to domestic violence survivors, from Unites States immigration law. Finally, this article discusses how this precedent will affect the future of immigration law and its effect on natives of other countries.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.035 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".