Gender Differences in Strain, Negative Emotions, and Coping Behaviors: A General Strain Theory Approach
Bibliographic record
Abstract
This paper empirically evaluates Broidy and Agnew’s propositions, in which they apply general strain theory to explain gender differences in crime and deviance, by analyzing data from a national survey of adult African Americans. First, African American women were more likely to report strains related to physical health, interpersonal relations, gender roles in the family, and less likely to mention work‐related, racial as well as job strain than African American men. Second, African American women were less likely than African American men to turn to deviant coping strategies when they experienced strain partly because their strains were more likely to generate self‐directed emotions, such as depression and anxiety, which in turn were less likely to lead to deviant coping behaviors than other‐directed, angry emotion. Finally, it was found that the self‐directed emotions were more likely to result in nondeviant, legitimate coping behaviors than other‐directed emotion, anger.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".