Operationalizing positive masculinity: a theoretical synthesis and school-based framework to engage boys and young men
Bibliographic record
Abstract
Scholars have consistently documented the relationship between conformity to traditional masculine norms and maladaptive psychosocial outcomes among boys and young men. Given current social commentary, including debate around 'toxic masculinity', intervention is needed to encourage boys to embody healthy expressions and identities of masculinity. Whilst new approaches grounded in positive masculinity show promise, the construct requires further definition and phenomenological clarity. Here we review divergent perspectives on positive masculinity, and forward a refined definition, specific to psychosocial health promotion among boys and young men. We then outline the theoretical basis of a positive masculinity framework to guide the content of future interventions, aiming to achieve positive identity development among boys and young men for the good of all. This framework represents a necessary unification of scholarship around male adolescent development, education and health. Future health promotion interventions may benefit from applying the framework to support a positive psychosocial trajectory among boys and young men, with a focus on connection, motivation and authenticity.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".