Intergroup bias toward “Group X”: Evidence of prejudice, dehumanization, avoidance, and discrimination against asexuals
Bibliographic record
Abstract
Although biases against homosexuals (and bisexuals) are well established, potential biases against a largely unrecognized sexual minority group, asexuals , has remained uninvestigated. In two studies (university student and community samples) we examined the extent to which those not desiring sexual activity are viewed negatively by heterosexuals. We provide the first empirical evidence of intergroup bias against asexuals (the so-called “Group X”), a social target evaluated more negatively, viewed as less human, and less valued as contact partners, relative to heterosexuals and other sexual minorities. Heterosexuals were also willing to discriminate against asexuals (matching discrimination against homosexuals). Potential confounds (e.g., bias against singles or unfamiliar groups) were ruled out as explanations. We suggest that the boundaries of theorizing about sexual minority prejudice be broadened to incorporate this new target group at this critical period, when interest in and recognition of asexuality is scientifically and culturally expanding.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".