An Assessment of Community Health Needs Assessment (CHNA) Data Collection Related to Building Capacity for Sexual and Gender Marginalized (SGM) Individuals in Health Care Organizations
Bibliographic record
Abstract
This research examines LGBTQ+ data collection for Community Health Needs Assessments (CHNA) by Wisconsin Health care organizations as mandated by the Affordable Care Act, and whether data collection considered LGBTQ+ populations. If collected, it assesses what types of LGBTQ+ data was collected and how it was used and/or reported in the CHNA. Furthermore, a comparison by location (rural/urban) regarding whether there is a difference in likelihood that a health care organization would collect LGBTQ+ data. The results of this study indicate that data collection is collected by approximately one-quarter of Wisconsin health care organizations for the purpose of their CHNAs and there is not a significant difference by location regarding inclusion of LGBTQ+ data.
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How this classification was reachedexpand
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 | 0.007 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".