Changes in Community Socioeconomic Status and Racial Distribution Associated With Gonorrhea Rates: An Analysis at the Community Level
Bibliographic record
Abstract
BACKGROUND: Gonorrhea persists despite nationwide disease control measures. Research has not focused on the longitudinal impact of community characteristics on gonorrhea. The authors assessed the association between community demographic and socioeconomic changes and gonorrhea rates. METHODS: Gonorrhea incident cases reported in 1992-1993 and 2001-2002 were aggregated at the census tract level in New York State exclusive of New York City and then matched to the census data. Census tract characteristics were obtained from the 1990 and 2000 decennial censuses and adjusted for changes in geographic boundaries. RESULTS: Gonorrhea incidence declined considerably between 2 study periods (1992-1993 and 2001-2002) among urban census tracts, but gradually increased in suburbs and rural areas. Changes in community socioeconomic status (SES) were significantly associated with change in gonorrhea rates (e.g., gonorrhea rate ratio given a 5% increase in household poverty rate = 1.08; 95% confidence interval: 1.02-1.14), independent of changes in community demographics. Increases in gonorrhea rates related to the proportion of non-Hispanic black population within urban census tracts persisted after multiple SES variables were controlled (rate ratio = 1.20; 95% confidence interval: 1.16-1.24). DISCUSSION: This study found that temporal changes in community SES and demographic characteristics were associated with changes in gonorrhea rates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".