Racial and ethnic disparities in long-term contraception use among the birthing population at an academic hospital in the Southeastern United States
Bibliographic record
Abstract
Ensuring women and birthing people have access to the contraceptive of their choice is essential for patient-centered care, health equity, and reproductive justice. While trends in national data in the United States reveal racial disparities in long-term contraceptive use, health-system and hospital-level investigations are essential to understand disparities and encourage interventions. We used data from 5011 patients who delivered at a large academic hospital to determine the effect of race/ethnicity and social vulnerability index (SVI) on the odds of undergoing a long-term contraceptive procedure. Results indicate that SVI substantially affects the odds of long-term contraception for non-Hispanic White women and birthing people. In contrast, Hispanic and non-Hispanic Black women and birthing people have significantly higher odds of undergoing a long-term contraceptive procedure due to race/ethnicity. Contributions to these disparities may be based on factors including healthcare providers, organizational and external policies. Interventions at all levels of care are essential to address disparities in contraceptive care, outcomes, and patient experience.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".