Integrating gender and sex to unpack trends in sexually transmitted infection surveillance data in British Columbia, Canada: an ethno-epidemiological study
Bibliographic record
Abstract
OBJECTIVES: Surveillance data frequently indicate that young men and women experience high-yet considerably different-reported rates of sexually transmitted infections (STIs), including bacterial infections such as chlamydia. We examined how several sex-based (eg, biological) and gender-based (eg, sociocultural) factors may interact to influence STI surveillance data trends. METHODS: Employing ethno-epidemiological techniques, we analysed cross-sectional qualitative data collected between 2006 and 2013 about young people's experiences accessing STI testing services in five communities in British Columbia, Canada. These data included 250 semistructured interviews with young men and women aged 15-24 years, as well as 39 clinicians who provided STI testing services. RESULTS: The findings highlight how young women are socially and medically encouraged to regularly test, while young men are rarely offered similar opportunities. Instead, young men tend to seek out testing services: (1) at the beginning or end of a sexual relationship; (2) after a high-risk sexual encounter; (3) after experiencing symptoms; or (4) based on concerns about 'abnormal' sexual anatomy. Our results illustrate how institutions and individuals align with stereotypical gender norms regarding sexual health responsibilities, STI testing and STI treatments. While these patterns reflect social phenomena, they also appear to intersect with sex-based, biological experiences of symptomatology in ways that might help to further explain systematic differences between young men's and women's patterns of testing for STIs. CONCLUSIONS: The results point to the importance of taking a social and biological view to understanding the factors that contribute to the gap between young men's and women's routine engagement in STI care.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".