Social epidemiology of gender diversity in early adolescents
Bibliographic record
Abstract
BACKGROUND: Few large U.S. cohort studies have examined multidimensional measures of gender diversity; therefore, this study investigates their associations with sociodemographic factors in a national sample of 12- to 13-year-old adolescents. METHODS: We conducted a cross-sectional analysis of Adolescent Brain Cognitive Development (ABCD) Study data (2019-2021, Year 3 follow-up, N = 10,089). Associations between sociodemographic characteristics and gender were evaluated using ordinal logistic regression for ordinal measures (gender non-contentedness and gender expression), multinomial regression models for categorical measures (transgender identity and felt gender), and linear regression models for continuous measures (felt gender and gender spectrum). RESULTS: Gender spectrum measures revealed the most diverse responses: 25.9% of sex-assigned females self-describing masculinity and 9.9% of sex-assigned males self-describing femininity. Female sex assigned at birth was associated with greater gender-diverse responses across all continuous and categorical gender measures compared to male sex assigned at birth. Higher household income was associated with less gender diversity relative to lower household income. CONCLUSION: Assessment of gender across multiple measures beyond binary gender identity (e.g., transgender vs. cisgender) may yield more diversity of responses in early adolescents. Future research could explore explanations for the sociodemographic factors associated with greater gender diversity in early adolescents. IMPACT: Our study uses a large and diverse cohort to analyze sociodemographic associations with gender diversity using multidimensional measures. Across gender measures, female sex assigned at birth and lower household income were associated with greater gender diversity. Future research on gender diversity in early adolescents should use multidimensional gender measures to better understand the nuances of gender development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".