Information, regulation and coordination: realist analysis of the efforts of community health committees to limit informal health care providers in Nigeria
Bibliographic record
Abstract
One of the consequences of ineffective governments is that they leave space for unlicensed and unregulated informal providers without formal training to deliver a large proportion of health services. Without institutions that facilitate appropriate health care transactions, patients tend to navigate health care markets from one inappropriate provider to another, receiving sub-optimal care, before they find appropriate providers; all the while incurring personal transaction costs. But the top-down interventions to address this barrier to accessing care are hampered by weak governments, as informal providers are entrenched in communities. To explore the role that communities could play in limiting informal providers, we applied the transaction costs theory of the firm which predicts that economic agents tend to organise production within firms when the costs of coordinating exchange through the market are greater than within a firm. In a realist analysis of qualitative data from Nigeria, we found that community health committees sometimes seek to limit informal providers in a manner that is consistent with the transaction costs theory of the firm. The committees deal not through legal sanction but by subtle influence and persuasion in a slow and faltering process of institutional change, leveraging the authority and resources available within their community, and from governments and NGOs. First, they provide information to reduce the market share controlled by informal providers, and then regulation to keep informal providers at bay while making the formal provider more competitive. When these efforts are ineffective or insufficient, committees are faced with a "make-or-buy" decision. The "make" decision involves coordination to co-produce formal health services and facilitate referrals from informal to formal providers. What sometimes results is a quasi-firm-informal and formal providers are networked in a single but loose production unit. These findings suggest that efforts to limit informal providers should seek to, among other things, augment existing community responses.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".