Action embellishment: An intention bias in the perception of success.
Bibliographic record
Abstract
Naïve theories of behavior hold that actions are caused by an agent's intentions, and the subsequent success of an action is measured by the satisfaction of those intentions. However, when an action is not as successful as intended, the expected causal link between intention and action may distort perception of the action itself. Four studies found evidence of an intention bias in perceptions of action. Actors perceived actions to be more successful when given a prior choice (e.g., choose between 2 words to type) and also when they felt greater motivation for the action (e.g., hitting pictures of disliked people). When the intent was to fail (e.g., singing poorly), choice led to worse estimates of performance. A final experiment suggested that intention bias works independent from self-enhancement motives. In observing another actor hit pictures of Hillary Clinton and Barack Obama, shots were distorted to match the actor's intentions, even when it opposed personal wishes. Together these studies indicate that judgments of action may be automatically distorted and that these inferences arise from the expected consistency between intention and action in agency.
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".