Gender-related variables for health research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In this paper, we argue for Gender as a Sociocultural Variable (GASV) as a complement to Sex as a Biological Variable (SABV). Sex (biology) and gender (sociocultural behaviors and attitudes) interact to influence health and disease processes across the lifespan-which is currently playing out in the COVID-19 pandemic. This study develops a gender assessment tool-the Stanford Gender-Related Variables for Health Research-for use in clinical and population research, including large-scale health surveys involving diverse Western populations. While analyzing sex as a biological variable is widely mandated, gender as a sociocultural variable is not, largely because the field lacks quantitative tools for analyzing the influence of gender on health outcomes. METHODS: We conducted a comprehensive review of English-language measures of gender from 1975 to 2015 to identify variables across three domains: gender norms, gender-related traits, and gender relations. This yielded 11 variables tested with 44 items in three US cross-sectional survey populations: two internet-based (N = 2051; N = 2135) and a patient-research registry (N = 489), conducted between May 2017 and January 2018. RESULTS: Exploratory and confirmatory factor analyses reduced 11 constructs to 7 gender-related variables: caregiver strain, work strain, independence, risk-taking, emotional intelligence, social support, and discrimination. Regression analyses, adjusted for age, ethnicity, income, education, sex assigned at birth, and self-reported gender identity, identified associations between these gender-related variables and self-rated general health, physical and mental health, and health-risk behaviors. CONCLUSION: Our new instrument represents an important step toward developing more comprehensive and precise survey-based measures of gender in relation to health. Our questionnaire is designed to shed light on how specific gender-related behaviors and attitudes contribute to health and disease processes, irrespective of-or in addition to-biological sex and self-reported gender identity. Use of these gender-related variables in experimental studies, such as clinical trials, may also help us understand if gender factors play an important role as treatment-effect modifiers and would thus need to be further considered in treatment decision-making.
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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 | 0.001 | 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) | 0.000 | 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 it