Social network analysis and realist evaluation have largely evolved in parallel despite shared concerns with complexity, conditionality, and interdependence. This article argues that integrating them can strengthen realist practice by making relational context more empirically visible and causal explanations more precisely specified. Context is conceptualized at two levels: national political and regulatory conditions that shape interorganizational networks, and realized network structures of centrality, community configuration, and brokerage that create relational opportunities and constraints. Network positions are treated as structural conditions that may provide access to resources, not as mechanisms in themselves. Realist evaluation is then used to investigate how actors interpret and use these opportunities and what mechanisms and outcomes follow. Drawing on a policy-influencing network study in the country of Georgia, the article shows how social network analysis can strengthen realist inquiry by identifying relational opportunities and constraints within complex multi-actor systems.
While transformation-focused evaluation is thriving in theory, less attention has been paid to how such approaches become institutionalised in governmental evaluation systems. Evaluation systems do not align well with transformation thought. In accordance with institutional theory, we propose ‘layering’ and ‘conversion’ as key mechanisms for expanding evaluation systems. We use three reflexive evaluations at the PBL Netherlands Environmental Assessment Agency as illustrative case studies. Using an interpretive research approach, we reconstructed stages and processes of institutionalisation over the past 10 years. Our findings demonstrate how reflexive evaluation has (a) expanded the learning function in alignment with the accountability purpose that evaluation primarily serves in policy cycles and (b) introduced quality norms and infrastructure to endorse this learning function during policy processes. We suggest further inquiry and debate on the drivers behind the opening up of conceptions of what evaluation is and should achieve in the wider governance system.
Evaluation approaches, or paradigms, are best understood as lenses: ways of looking at evaluands that are chosen, not inevitable. Framing them this way presents evaluation traditions as options to be selected rather than positions to be defended, inviting evaluators to ask not ‘which paradigm is correct?’ but ‘which lens best serves this evaluation’s context and purpose?’ The lens metaphor offers two practical benefits. First, it promotes flexibility, encouraging evaluators to expand their repertoire and guiding them towards the right lens for each situation. Second, it offers a common framework for exploring what evaluation is, making convergence and divergence across paradigms more apparent and improving evaluative discourse and practice. The paper compares six approaches: a-theoretical (or accountability), experimental, realist, constructivist, pragmatic, and systems evaluation, across 10 dimensions, including purpose, causality, validity, and each lens’s blind spot. The aim is not to resolve paradigm debates but to structure them usefully.
This article analyzes local policy evaluation in China through 415 policy documents (2003–2026) and a four-dimensional framework covering institutional impetus, policy domains, evaluation timing, and intended use. Using temporal, content, and thematic analysis, it finds three stages of development: formation, growth, and deepening. Local policy evaluation has moved from scattered experimentation to broader cross-sectoral expansion and fuller policy embedding. The study argues that this evolution has been driven mainly by administrative authorization, hierarchical transmission, and local adaptation. Evaluation often enters governance first as a procedural arrangement, with stronger findings-oriented use developing later. Three challenges remain: a weak localized knowledge system, underdeveloped feedback mechanisms, and an immature evaluation culture.
Assessing social impact remains challenging for small-scale, early-stage projects in low- and middle-income countries (LMICs), where existing Social Impact Assessment (SIA) frameworks are often too complex for organizations with limited capacity. This study develops a flexible SIA Application System tailored to innovation-oriented pilot projects operating under high uncertainty in LMICs. Refined through a qualitative case study of the Global Innovation Fund—using semi-structured interviews and document analysis across agriculture, water, and electricity sectors—the system integrates three components: (1) a refined framework of core assessment dimensions; (2) a structured process for local scoping and indicator selection; and (3) adaptive functions aligning assessment with project maturity, from pre-pilot to post-pilot phases. By repositioning SIA as a staged, learning-oriented process, the system balances feasibility and accountability, offering a practical tool for adaptive decision-making in high-uncertainty LMIC pilot contexts.
