Bibliographic record
Abstract
For readers concerned about LGBTQ rights and the history of U.S. citizenship policies, get the book that Booklist says is "insightful" and "an accessible human story with a happy ending." The January 2018 headline story in the Los Angeles Times was riveting. Andrew from the United States and Elad Dvash-Banks from Israel married in Canada in 2010 when gay couples could not marry in these countries. The couple conceived fraternal twins, Aiden and Ethan, with a Canadian surrogate by means of egg and sperm donation. The two boys were born just four minutes apart. Aiden was conceived with a donated egg and Andrew's sperm cell, and Ethan was conceived with a donated egg (from the same woman) and Elad's sperm cell. Andrew and Elad wished to raise their children in the United States, but when they arrived at the American Consulate in Toronto to apply for citizenship, a staff member fired off a series of “shocking” and humiliating questions, and informed the couple of her authority to require a DNA test to determine each parents’ relatedness to each twin—she warned that without these tests neither twin would be granted US citizenship. Andrew and Elad knew which twin each had fathered and had planned on keeping this information confidential. They knew this because DNA analyses had already been performed, but the consulate insisted that these costly tests be repeated using their designated laboratory. Having no alternative, DNA testing was arranged, and results submitted to the consulate. Soon, two envelopes arrived at their home, bearing both welcome and dreaded news: United States citizenship was offered to Aiden, whose father was a US citizen, but not to Ethan, whose father was Israeli. And, thus, their ground-breaking legal journey began. The couple’s high-profile lawsuit nearly reached the US Supreme Court, capturing worldwide attention along the way. Nancy Segal brings the story to life through firsthand accounts of each father’s life history and analysis of the legal intricacies that threatened to deny US citizenship to one of their twin sons.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.010 |
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".