Love is Not Colorblind: An Investigation of the Racial Hierarchy of Mate Preferences
Bibliographic record
Abstract
Not my type is the usual invocation when rejecting potential lovers who don’t align with the racial hierarchy of mating preferences. The largely unchallenged norm of interracial intimacy aversion, particularly how the desire for some racial groups and rejection of others reinforces existing racial inequities, is inconsistent with the blanket notion of greater interracial acceptance. Our investigation assessed the openness of monoracial and multiracial individuals to form interracial romantic relationships. We partially replicated an interracial mate preference known as the Multiracial Dividend Effect, finding that most monoracial groups equally preferred same-race lovers and interracially dating multiracials, and they preferred interracially dating someone multiracial over any monoracial group, whereas Multiracials were more open to interracially dating any monoracial group than monoracials were to interracially date each other. In addition, Hispanic-White and East Asian-White multiracials were more open to interracially dating White individuals than their respective monoracial in-group members, and East Asian-White multiracials were more open to interracially dating all monoracial minority groups than monoracial East Asian participants. Finally, half-White multiracials are more likely to be in partial-racial couples (e.g., former President of the United States Barack Obama is Black-White multiracial and the former First Lady of the United States, Michelle Obama, is Black) whereas interminority multiracials are more likely to be in 100% interracial/non-overlapping couples (e.g., Vice President of the United States Kamala Harris is interminority Tamil Indian and Black whereas the Second Gentleman of the United States, Doug Emhoff, is White).
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.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".