Accountability mechanisms and the value of relationships: experiences of front-line managers at subnational level in Kenya and South Africa
Bibliographic record
Abstract
Resource constraints, value for money debates and concerns about provider behaviour have placed accountability 'front and centre stage' in health system improvement initiatives and policy prescriptions. There are a myriad of accountability relationships within health systems, all of which can be transformed by decentralisation of health system decision-making from national to subnational level. Many potential benefits of decentralisation depend critically on the accountability processes and practices of front-line health facility providers and managers, who play a central role in policy implementation at province, county, district and facility levels. However, few studies have examined these responsibilities and practices in detail, including their implications for service delivery. In this paper we contribute to filling this gap through presenting data drawn from broader ongoing research collaborations between researchers and health managers in Kenya and South Africa. These collaborations are aimed at understanding and strengthening day-to-day micropractices of health system governance, including accountability processes. We illuminate the multiple directions and forms of accountability operating at the subnational level across three sites. Through detailed illustrative examples we highlight some of the unintended consequences of bureaucratic forms of accountability, the importance of relational elements in enabling effective bureaucratic accountability, and the ways in which front-line managers can sometimes creatively draw upon one set of accountability requirements to challenge another set to meet their goals. Overall, we argue that interpersonal interactions are key to appropriate functioning of many accountability mechanisms, and that policies and interventions supportive of positive relationships should complement target-based and/or audit-style mechanisms to achieve their intended effects. Where this is done systematically and across key elements and actors of the health system, this offers potential to build everyday health system resilience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".