Genetic Options: The Impact of Genetic Ancestry Testing on Consumers’ Racial and Ethnic Identities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The rapid growth of genetic ancestry testing has brought concerns that these tests will transform consumers’ racial and ethnic identities, producing “geneticized” identities determined by genetic knowledge. Drawing on 100 qualitative interviews with white, black, Hispanic/Latino, Asian, and Native Americans, the authors develop the genetic options theory to account for how genetic ancestry tests influence consumers’ ethnic and racial identities. The theory maintains that consumers do not accept the tests’ results as given but choose selectively from the estimates according to two mechanisms: their identity aspirations and social appraisals. Yet consumers’ prior racialization also influences their identity aspirations; white respondents aspired to new identities more readily and in substantively different ways. The authors’ findings suggest that genetic ancestry testing can reinforce race privilege among those who already experience it.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it