Community Health Centers (CHCs) Under Environmental Uncertainty: An Examination of the Affordable Care Act of 2010 and Early Medicaid Expansion on CHC Margin
Bibliographic record
Abstract
Abstract Nonprofit community health centers (CHCs) are the largest subset of safety net clinics in the United States and, in many vulnerable and underserved areas, act as the only provider of vital health services in the community. The expansion of Medicaid provision under the Affordable Care Act of 2010 led to a fundamental change in the core client demographics of CHCs, with higher income thresholds and single childless individuals now eligible for Medicaid. This expansion of the Medicaid population creates both opportunities and threats that may impact CHCs’ long term financial sustainability. Accumulating reserves through positive net margins is a managerial tactic that nonprofits can utilize to buffer against environmental uncertainty. This study utilizes data from IRS Form 990s, American Community Survey, HRSA grantee lists, and the Area Resource File to model the differences in net margins between CHCs in early Medicaid expansion and non-expansion states from 2008–2012. Results show higher margins for CHCs in early expansion states compared to non-expansion states, even after accounting for organizational and environmental covariates. CHCs who are HRSA grantees are associated with positive margins whereas those relying more heavily on program revenue show negative margins. Further, CHCs located in counties with higher percentages of persons in poverty also demonstrate reduced margins. This exploratory study contributes to the nonprofit finance literature by highlighting the importance of incorporating contextual variables to deepen our understanding of changes in nonprofit financial health.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".