Proximal and Distal Intent: Toward a New Folk Theory of Intentional Action
Bibliographic record
Abstract
Inferences regarding actors’ intentions play an important role in social and moral cognition. Numerous studies have operationalized intentionality in a binary fashion (i.e., an act is either “intentional” or “unintentional”). The authors suggest, however, that when determining the degree to which an act was intentional, lay observers consider two independent dimensions: proximal intent (the actor's focus on the means) and distal intent (the actor's focus on the end). They describe how the proximal intent/distal intent (PIDI) approach allows researchers to understand observers’ intent-related judgments with greater precision. The authors review studies highlighting a range of variables that lead perceivers to prioritize either proximal intent or distal intent in their social and moral judgment. They describe how previous findings in the literature may be reinterpreted in light of the PIDI framework. Finally, they suggest ways in which the PIDI framework implies novel directions for future research on moral cognition.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.023 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".