Adoption and Multiculturalism: Europe, the Americas, and the Pacific
Bibliographic record
Abstract
Adoption and Multiculturalism features the voices of international scholars reflecting transnational and transracial adoption and its relationship to notions of multiculturalism. The essays trouble common understandings about who is being adopted, who is adopting, and where these acts are taking place, challenging in fascinating ways the tidy master narrative of saviorhood and the concept of a monolithic Western receiving nation. Too often the presumption is that the adoptive and receiving country is one that celebrates racial and ethnic diversity, thus making it superior to the conservative and insular places from which adoptees arrive. The volume’s contributors subvert the often simplistic ways that multiculturalism is linked to transnational and transracial adoption and reveal how troubling multiculturalism in fact can be.\nThe contributors represent a wide range of disciplines, cultures, and connections in relation to the adoption constellation, bringing perspectives from Europe (including Scandinavia), Canada, the United States, and Australia. The book brings together the various methodologies of literary criticism, history, anthropology, sociology, and cultural theory to demonstrate the multifarious and robust ways that adoption and multiculturalism might be studied and considered. Edited by three transnational and transracial adoptees, Adoption and Multiculturalism: Europe, the Americas, and the Pacific offers bold new scholarship that revises popular notions of transracial and transnational adoption as practice and phenomenon.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".