A conceptualisation of scale-up and sustainability of social innovations in global health: a narrative review and integrative framework for action
Bibliographic record
Abstract
BACKGROUND: The scale-up and sustainability of social innovations for health have received increased interest in global health research in recent years; however, these ambiguous concepts are poorly defined and insufficiently theorised and studied. Researchers, policymakers, and practitioners lack conceptual clarity and integrated frameworks for the scale-up and sustainability of global health innovations. Often, the frameworks developed are conceived in a linear and deterministic or consequentialist vision of the diffusion of innovations. This approach limits the consideration of complexity in scaling up and sustaining innovations. OBJECTIVE: By using a systems theory lens and conducting a narrative review, this manuscript aims to produce an evidence-based integrative conceptual framework for the scale-up and sustainability of global health innovations. METHOD: We conducted a hermeneutic narrative review to synthetise different definitions of scale-up and sustainability to model an integrative definition of these concepts for global health. We have summarised the literature on the determinants that influence the conditions for innovation success or failure while noting the interconnections between internal and external innovation environments. RESULTS: The internal innovation environment includes innovation characteristics (effectiveness and testability, monitoring and evaluation systems, simplification processes, resource requirements) and organisational characteristics (leadership and governance, organisational change, and organisational viability). The external innovation environment refers to receptive and transformative environments; the values, cultures, norms, and practices of individuals, communities, organisations, and systems; and other contextual characteristics relevant to innovation development. CONCLUSION: From these syntheses, we proposed an interconnected framework for action to better guide innovation researchers, practitioners, and policymakers in incorporating complexity and systemic interactions between internal and external innovation environments in global health.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".