Does Experience of Failure Decrease Executive, Regulatory Abilities and Increase Aggression?
Bibliographic record
Abstract
Recent advances in the study of affective-cognitive regulation of aggressive behavior suggest positive correlations between poor executive capacities (ECF) and dispositional negative reactivity (Posner & Rothbart, 2000). If the global assumption is correct what are the likely implications of predicted relation? The central issue in present research was to verify this assumption and examine how situational characteristics could alter executive performance in persons with Dysexecutive Syndrome (DES, Baddeley, 1998) and healthy adults (students, health workers) to explore some of the consequences of those modifications for aggressive tendencies. Precisely, we expected the positive correlations between poor executive performances and high aggressive tendencies at dispositional as well situational levels, except for health workers, given their professional duties. In order to assess cognitive capacities and dispositional as well as situational aggressive tendencies, during two studies (First study: N=60 students; Second study: N= 60 students, N= 24 patient with Dysexecutive Syndrome, ; N= 45 health care workers) right-handed French-speakers participants completed twice, during an initial phase of the study and one week after, a series of standard executive functions neuropsychological tests and aggression questionnaires. During second phase, participants executed a task introducing the experimental feedbacks (success, neutral, failure) before completion of neuropsychological tests and questionnaires. The results provided evidence of a dispositional relationship between poor executive functioning and aggressive tendencies, and extended it to situational level. For all participants, it showed that increases in impulsiveness (negative emotionality and aggressive choices) due to a negative feedback were concomitant with an inability to focus individuals' attention on ongoing tasks.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".