Poor medicine for poor people? Assessing the impact of neoliberal reform on health care equity in a post-socialist context
Bibliographic record
Abstract
Driven in part by a resurgent interest in social inequality and health, and in part by increasing scrutiny of the social and health consequences of neoliberal economic reform, principles of health equity and social justice, the centerpieces of the Health for All strategy drafted at Alma Ata in 1978, are once again at center stage in global public health debates. Whether and how equity in access to health care can be maintained in a context of market-based health sector reform has not been systematically addressed, particularly from the perspective of local communities. This paper will explore how health reform affects health care in post-socialist Mongolia. Through a mixed-methods household-based study of low-to-middle income communities in urban and rural Mongolia we find that despite explicit and concerted efforts to reduce inequities, the reform system is unable to provide equitable health care either vertically or horizontally. Emphasis on privatization of the secondary and tertiary sectors of the system, coupled with deployment of universally-accessible, but from a clinical standpoint, limited, version of essential primary care, produces a fragmented system. Particularly for the vulnerable poor, access to services beyond the primary care system is compromised by financial, opportunity, and informational cost barriers. This research suggests that new models of health reform are needed that will effectively bridge the growing gaps between public and private resources, primary and secondary and/or tertiary care, and clinical and public health services.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.006 |
| 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".