Bibliographic record
Abstract
While international adoptions have risen in the public eye and recent scholarship has covered transnational adoption from Asia to the U.S., adoptions between North America and Latin America have been overshadowed and, in some cases, forgotten. In this nuanced study of adoption, Karen Dubinsky expands the historical record while she considers the political symbolism of children caught up in adoption and migration controversies in Canada, the United States, Cuba, and Guatemala.Babies without Borders tells the interrelated stories of Cuban children caught in Operation Peter Pan, adopted Black and Native American children who became icons in the Sixties, and Guatemalan children whose disappearance today in transnational adoption networks echoes their fate during the country s brutal civil war. Drawing from archival research as well as from her critical observations as an adoptive parent, Dubinsky moves debates around transnational adoption beyond the current dichotomy the good of humanitarian rescue, against the evil of imperialist kidnap. Integrating the personal with the scholarly, Babies without Borders exposes what happens when children bear the weight of adult political conflicts.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".