Exploring Dehumanization and Infrahumanization as Underlying Factors in Misinformation Belief and Spread
Bibliographic record
Abstract
An examination of the literature in misinformation research shows a gap in the area of dehumanization and the related phenomenon of infrahumanization, each of which demonstrates how individuals reduce the human characteristics of others in blatant or subtle ways. This paper examines dehumanizing and infrahumanizing behavior as potential motives and user characteristics in the spread of and belief in misinformation. It is theorized that attitudes expressed against outgroup members reflect the degree to which one infrahumanizes others, with the result that one might more willingly believe and spread misinformation about a targeted outgroup. This paper contributes to the literature in its suggestion of a novel and understudied area in misinformation, identifying key concepts and important considerations for advancing the field of misinformation studies. Exploration de la déshumanisation et de l'infrahumanisation comme facteurs pour la croyance et la propagation de désinformation RésuméUn examen de la littérature sur la recherche portant sur la désinformation révèle une lacune dans le domaine de la déshumanisation et le phénomène relié d'infrahumanisation, chacun démontrant comment les individus réduisent les caractéristiques humaines des autres de façon évidente ou subtile. Cet article analyse les comportements de déshumanisation et d'infrahumanisation comme motifs potentiels et caractéristiques des usagers dans la propagation et la croyance de la désinformation. Il est théorisé que les attitudes exprimées contre les membres hors-groupe reflètent le degré auquel une personne peut en infrahumaniser une autre, avec le résultat que quelqu'un est plus propice de croire et de propager de la désinformation à propos d'un groupe externe ciblé. Cet article contribue à la littérature par sa suggestion d'une zone nouvelle et sous-étudiée de la désinformation, en identifiant les concepts clés et d'importantes considérations pour l'avancement du domaine de l'étude de la désinformation. Mots-clésDésinformation; Déshumanisation; Infrahumanisation; Comportements informationnels
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".