Determined Yet Dehumanized: People Higher in Self-Control Are Seen as More Robotic
Bibliographic record
Abstract
Desire is part of human nature, and being vulnerable to desire is part of what differentiates humans from machines. However, individuals with high self-control—who demonstrate impressive resistance to their desires—may appear to lack such human vulnerability. We propose that people perceived as high in self-control tend to be dehumanized as more robotic, relating to potentially negative social consequences. Across six studies ( N = 2,007), people perceived those higher in self-control as more robotic. In addition, we found some evidence that this robotic-dehumanization was related to less interest in spending time with the high self-control person. This outcome was reliably linked to lower warmth perceptions that correlated with greater robotic-dehumanization. Together, our results offer new insights into the social dynamics of exhibiting high self-control.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".