Feeling Duped: Emotional, Motivational, and Cognitive Aspects of Being Exploited by Others
Bibliographic record
Abstract
Feeling duped is an aversive emotional response to the perception of having been taken advantage of in a interpersonal transaction (primarily those involving economic exchange), partly as a result of one's own decisions. The actual likelihood of being duped, as well as the heightened vigilance for it, should increase as a function of opportunity (e.g., information asymmetry that gives one side a big advantage in knowledge) and motivation (e.g., an exceptionally huge payoff may make it worth defrauding a long-term business partner). Being duped produces an aversive self-conscious emotion with a threat of self-blame. There appears to be stable individual differences in the motivation (called sugrophobia) to avoid being a sucker. High sugrophobes will be vigilant and skeptical of potential deals. Low sugrophobes may not even realize in some instances that they were duped. The aversive reaction to feeling duped stimulates counterfactual ruminations that may intensify sugrophobia but also aids in extracting useful lessons.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".