LEARNED VIOLENCE: BANDURA’S SOCIAL LEARNING THEORY IN EDWARD BOND'S THE CHILDREN
Bibliographic record
Abstract
This study focuses on Bandura's social learning theory by examining the theme of learned violence in Edward Bond's The Children. Albert Bandura, a significant Canadian-born American psychologist, studied behaviourist questions about individuals and developed what is now known as social learning theory. In response to the outdated belief that violent behaviour is the result of innate aggressive tendencies, he introduced the theory which is concerned with the interaction of the learner's mind and its surroundings. Bandura's theory posits that people learn new behaviour, attitudes, and emotional responses by observing, modelling, and imitating the actions of others in their social environment. Edward Bond, on the other hand, has been one of the most controversial and prolific writers in contemporary British theatre. His twelve-scene short play The Children, which premiered in 2000, is considered as one of his later works. By using young characters in his work, the playwright reflects on the effects of social environment on teenagers. The play is about Joe, a teenager who lives with his abusive mother. When compared to his mother, Joe becomes more violent over time because he burns down a building in which a child dies. Thus, Bond's play demonstrates how violence is learned in parallel with Bandura's theory.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".