Does Violent Movie Exposure Affect Aggressive Cognition of Chinese Adolescents? Evidences from a Modified STROOP Task
Bibliographic record
Abstract
The main purpose of the study was to examine the impact of violent movies on aggressive cognition of Chineseadolescents. A modified STROOP word-color naming task was used to examine whether aggressive words couldprime Chinese adolescents’ aggressive cognition. The result showed no significant differences in aggressivelyactivated score (AAS) for violent movie and non-violent movies, and that no significant differences were foundin main affect of movie type (violent movie vs. non-violent movie). However, it did reveal significant MovieType × Gender interaction, and that aggressive cognition was significantly affected by violent movie for boys,but was not for girls. Additionally, significant Movie Type × Aggressive Level interaction was found, and thataggressive cognition was significantly influenced by violent movie only for high-aggressive level (HL)participants, not for low-aggressive level (LL) and mid-aggressive level (ML) participants, which partlysupported General Aggressive Model (GAM). Limitations of the present study were also discussed.
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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) | 0.001 | 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".