Understanding driver anger and aggression: Attributional theory in the driving environment.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two studies tested the applicability of Weiner's (1995, 1996, 2001, 2006) attributional model of social conduct to roadway environments. This model highlights the role of inferences of responsibility after making causal judgments for social transgressions. Study 1 employed written scenarios where participants were asked to imagine themselves driving on a major highway. The degree of controllability and intentionality of the driving act was manipulated experimentally by altering the specific event-related details provided to the participants. Study 2 extended this research to life events by having participants complete online driving diaries every 2 days, identifying their most negative/upsetting encounter with another motorist. The most anger-provoking event was selected from among 4 diary entries and participants were asked to respond to a questionnaire similar to that used in Study 1. Path analyses in both studies generally supported predictions derived from Weiner's model; the association between perceived controllability, intentionality, and dispositional locus of causality of the negative driving event and subsequent anger was mediated by perceptions of responsibility. Additional results in Study 2 suggested that low perceived controllability, intentionality, and dispositional locus of causality were associated with reduced perceived responsibility, which, in turn, facilitated feelings of sympathy. Anger was associated with aggressive responses to the offending driver, whereas sympathy was associated with prosocial responses. Recommendations were offered for improved driver safety, including the development of attributional retraining programs to combat self-serving attributional biases, teaching novice drivers about both formal and informal roadway communication, and the promotion of forgiveness among drivers
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it