The Safety Net of the Safety Net: How Federally Qualified Health Centers "Subsidize" Medicaid Managed Care
Bibliographic record
Abstract
In this article, I examine the impact of neoliberalism and welfare reform on the delivery of Medicaid, specifically how the advent of Medicaid managed care (MMC) has been wrought with contradictions, placing increased burdens on primary safety-net organizations and impacting the many communities they serve. I argue that federally qualified health centers (FQHCs) operate as a primary safety net among safety-net providers, supporting and subsidizing New Mexico's MMC program financially and administratively. By presenting ethnographic data, I will demonstrate how FQHCs pay many of the hidden financial and institutional costs of the shift to managed care. Such findings uncover paradoxes inherent to neoliberal ideologies and privatization, raising questions about the efficacy of a managed care system for Medicaid as well as the future of the health care safety net and access to health care for the diverse populations it serves.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".