Explaining dehumanization among children: The interspecies model of prejudice
Bibliographic record
Abstract
Although many theoretical approaches have emerged to explain prejudices expressed by children, none incorporate outgroup dehumanization, a key predictor of prejudice among adults. According to the Interspecies Model of Prejudice, beliefs in the human-animal divide facilitate outgroup prejudice through fostering animalistic dehumanization (Costello & Hodson, 2010). In the present investigation, White children attributed Black children fewer 'uniquely human' characteristics, representing the first systematic evidence of racial dehumanization among children (Studies 1 and 2). In Study 2, path analyses supported the Interspecies Model of Prejudice: children's human-animal divide beliefs predicted greater racial prejudice, an effect explained by heightened racial dehumanization. Similar patterns emerged among parents. Furthermore, parent Social Dominance Orientation predicted child prejudice indirectly through children's endorsement of a hierarchical human-animal divide and subsequent dehumanizing tendencies. Encouragingly, children's human-animal divide perceptions were malleable to an experimental prime highlighting animal-human similarity. Implications for prejudice interventions are considered.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".