The role of group memberships and school identification on student well‐being
Bibliographic record
Abstract
There are widespread concerns about a decline in young people's mental health. One promising direction to address this issue involves group memberships and social identity processes. Despite progress, there are several issues in current theory and research including (1) whether the number of groups to which an individual belongs is related to more positive well-being, (2) better understanding the relationship between group memberships and social identification processes and (3) the need for more comprehensive longitudinal methods. The goal of this study was to address these issues using a three-wave longitudinal design (n = 1331) conducted with high-school students. Both the number and importance (an indicator of social identification) of student extracurricular activities (ECA) were assessed as predictors of six well-being outcomes. Importantly, we also assessed whether identification with the school as the context in which the ECAs were situated mediated this association. Results show that, generally, the number of group memberships had no direct effect on well-being, however, there was a consistent mediation via school identification. When considering number and importance of one model (comprising a subsample) importance emerged as the key predictor. Such findings advance understanding of the social identity and well-being relationship and have practical implications.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".