Gender and ethnicity: Are they associated with differential outcomes of a biopsychosocial social-emotional learning program?
Bibliographic record
Abstract
CONTEXT: Social-emotional learning (SEL) program outcomes may be enhanced when programs take into account gender and ethnicity differences, yet few studies directly examine these variables. The limited literature further suggests improved outcomes accrue by integrating physiological techniques, such as yoga and meditation, directly into SEL curricula to reduce stress. AIMS: This study investigated the association between outcomes of a yogic breath-based biopsychosocial SEL intervention across gender and ethnicity. METHODS: Fifty-nine high school students were evaluated on 4 positive (self-esteem, identity formation, anger coping ability, planning, and concentration) and 3 negative SEL outcomes (impulsivity, distractibility, and endorsement of aggression). Using a repeated-measures design, group differences between gender and ethnicity were assessed. RESULTS AND CONCLUSIONS: Significant improvements on all 7 outcomes were found for the sample, suggesting that participants performed better after the intervention. There were neither significant differences between males and females on outcomes nor between different ethnic groups with the exception of African-Americans scoring lower on one of three emotion regulation outcomes. This study, one of the first to directly analyze SEL outcomes by sociodemographic variables, demonstrated the program's biopsychosocial approach was associated with beneficial SEL outcomes across genders and ethnicities. Future studies of biopsychosocial programs taking into account sociodemographics will allow SEL programs to be more effective across diverse populations.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".