A Critical Adoption Dialogue about the Race-Family-Nation Nexus
Bibliographic record
Abstract
abstract: Adoption & Culture 's series of anniversary articles has affirmed critical adoption studies (CAS) as a growing, diverse, and continually relevant field of inquiry. As part of this endeavor, two adoption scholars created a collaborative dialogue on what it means to "do" CAS from the unique but overlapping perspectives of their two distinct research projects: Dorow's sociological work on late twentieth century China-US adoption and Stevenson's historical work on mid-twentieth century Indigenous adoption in Canada. Reflecting together on their respective approaches and methodologies, they focus on the intimate politics of kinship-nation-race that animate both of these contexts of adoption, while also noting the specific questions and issues that emerge from each distinct context. The conclusion offers three questions for the ongoing work of CAS and asserts the need for more interdisciplinary and pluralistic studies across seemingly disparate cases.
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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 | 0.045 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.079 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.013 | 0.018 |
| 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".