When Harry met Meghan (got married, had a baby, and “Megxited”): Intergroup anxiety, ingroup norms, and racialized categorization as predictors of receptivity to interracial romances
Bibliographic record
Abstract
Abstract Despite being frequently met with disapproval, interracial romantic relationships have the potential to transform intergroup relations through marriage and children. However, relatively little is known about the receptivity to these important intergroup relationships. Capitalizing on three historical events involving a world‐famous interracial couple, Prince Harry and Meghan, we expand the intergroup relations literature by longitudinally and cross‐sectionally examining White Briton's perceptions and receptivity to interracial romances. Study 1 ( N = 585) showed that intergroup anxiety around the couple's wedding was longitudinally associated with less receptivity to interracial dating and less favorable intergroup attitudes a month later, even when controlling for strong autoregressive paths. Study 2 ( N = 402), conducted around the birth of the couple's son (Archie), found that intergroup anxiety (negatively) and favorable ingroup norms (positively) were longitudinally associated with receptivity to intergroup romances and favorable intergroup attitudes a month later in statistically conservative tests. Study 3 ( N = 507), conducted at the time of the so‐called “Megxit,” cross‐sectionally found that media exposure to Meghan was positively associated with favorable ingroup norms which was, again, related to positive intergroup outcomes. However, these associations were suppressed by the perception that Meghan had tainted the Royal Family which was, in turn, negatively associated with the intergroup outcomes. Moderation analyses across the studies revealed these associations were often stronger for those who categorized the biracial Royals as more Black (vs. White). Together, the novel research highlights the often‐complex perceptions and longitudinal predictors of interracial romances and does so in historic social contexts.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".