DIFFERENCES IN CONFORMITY TO MASCULINE NORMS ACROSS AGE COHORTS
Bibliographic record
Abstract
Abstract Conformity to masculine norms is associated with worse mental health among men, but little is known about conformity to masculine norms across the lifespan. Much of the literature on this topic focuses on early adulthood, rarely extending past middle age. Research indicates that attaining hegemonic masculinity becomes more difficult as one ages. One study with Australian young and middle-aged men found that conformity to masculine norms was lower in middle-aged cohorts than in younger cohorts. A study of Canadian men aged 55 years and up found that conformity to masculine norms did not significantly differ between those aged 55-69 and those aged 70+ years. The present study assessed differences in conformity to masculine norms across the adult lifespan. It was hypothesized that scores on the conformity to masculine norms inventory (CMNI) would significantly differ across six age groups and would be lower in older cohorts. The mean CMNI score for males (N = 447) was 60.96 (SD = 19.09) and for females (N = 431) was 47.19 (SD = 15.11). In a one-way ANOVA, scores significantly differed between age cohorts for the male (F(5, 441) = 20.83, p < .001) and female samples (F(5,425) = 14.85, p < .001). Tukey’s HSD test for multiple comparisons revealed that CMNI scores were significantly lower in older cohorts compared to younger cohorts in both males and females. Findings highlight the importance of considering age-related differences in the presentation of masculinity. Future studies should investigate whether differences are related to aging or cohort effects.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".