Geography of primary healthcare in Forsyth County, North Carolina
Bibliographic record
Abstract
Health care in the United States has been a contentious subject for many years and various aspects of health care have been subject to numerous legislative debates, news pieces, and research papers. One subject that has not been focused on enough is primary healthcare accessibility in small and medium urban areas. This study seeks to fill in the gap with a focus on Forsyth County, North Carolina, a medium sized county. This study uses Geographic Information Science (GIS) to measure the distance from Census block groups to the nearest primary care facility. Data used for analysis included primary care facilities in Forsyth County and facilities just outside of the county limits. Block group demographic data was obtained from the United States Census Bureau. Most block groups in Forsyth County were close to a facility with most being around one mile to the nearest facility. The county’s biggest city, Winston-Salem, had the most facilities and were the closest to facilities overall. The rural edges of the county had fewer facilities and were further away from facilities. This study does not account from population behavior, as residents may not use their nearest facility. Factors for this include cost and transportation. This study does provide a foundation for future studies in Forsyth County and in other small and medium sized urban areas.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".