Family Matters: Examining Family Racial Identity Invalidation Among Biracial People
Bibliographic record
Abstract
Abstract A common racial stressor for Multiracial people is racial identity invalidation: the experience of having one’s racial identity denied by others. This preregistered, exploratory study investigated Biracial people’s experiences of identity invalidation within a family setting. We used a sample of 383 Biracial adults ( M age = 21.3, SD = 5.8; 72.3% female; 25.8% male; 1.9% transgender/gender non-conforming) to examine the frequency of family racial identity invalidation, its associations with family relations and psychosocial well-being, and characteristics of family members who perpetrated invalidation. Nearly half of participants reported racial identity invalidation from at least one family member, and this rate did not differ between Biracial subgroups (Asian-White, Latine-White, Black-White, Black-Minority, Other minority-White). Within the Latine-White subgroup, family invalidation was negatively associated with family relations and psychosocial well-being. Participants across all subgroups reported experiencing invalidation more frequently from extended family members (e.g., grandparents, aunts/uncles, etc.), compared to immediate family members. However, participants reported invalidation from White and racial minority relatives at similar frequencies. These findings emphasize the salience of extended family members in understanding Multiracial people’s experiences of racial identity invalidation. This study also highlights the need for further research on specific Multiracial subgroups, particularly among Latine-White people.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".