Bridging Boundaries? The Effect of Genetic Ancestry Testing on Ties across Racial Groups
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
Abstract The phenomenon of widespread genetic ancestry testing has raised questions about its social impact, particularly on issues of race. Some accounts suggest testing can promote bridging social capital – connections between racial groups. In this multi-method paper, we ask whether (1) taking genetic ancestry tests (GATs) and (2) receiving results of African, Asian, or Native American ancestry increases network racial diversity for White Americans. We use a randomized controlled trial of 802 White, non-Hispanic Americans, half of whom received GATs. Unexpected findings show that test-takers’ network racial diversity decreases after testing. Using 58 follow-up interviews, we develop and test a possible theory, finding initial evidence that test-takers’ network racial diversity declines because they reconsider their racial appraisals of others in their networks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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