Signaling virtuous victimhood as indicators of Dark Triad personalities.
Bibliographic record
Abstract
We investigate the consequences and predictors of emitting signals of victimhood and virtue. In our first three studies, we show that the virtuous victim signal can facilitate nonreciprocal resource transfer from others to the signaler. Next, we develop and validate a victim signaling scale that we combine with an established measure of virtue signaling to operationalize the virtuous victim construct. We show that individuals with Dark Triad traits-Machiavellianism, Narcissism, Psychopathy-more frequently signal virtuous victimhood, controlling for demographic and socioeconomic variables that are commonly associated with victimization in Western societies. In Study 5, we show that a specific dimension of Machiavellianism-amoral manipulation-and a form of narcissism that reflects a person's belief in their superior prosociality predict more frequent virtuous victim signaling. Studies 3, 4, and 6 test our hypothesis that the frequency of emitting virtuous victim signal predicts a person's willingness to engage in and endorse ethically questionable behaviors, such as lying to earn a bonus, intention to purchase counterfeit products and moral judgments of counterfeiters, and making exaggerated claims about being harmed in an organizational context. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".