The methodological backbone of the study is qualitative document analysis, a technique that allows researchers to extract patterns of institutional behavior from policy papers, project records, and publicly available reports without relying on interviews or fieldwork. Because the study relied exclusively on publicly available documents and institutional records, no human participants were involved and no personal or confidential data were collected, which meant formal ethical approval was not required. This documentary approach has particular advantages in fragile states, where insecurity can make direct data collection difficult and where the written record of aid agreements, development plans, and municipal budgets often constitutes the most reliable evidence of how governance actually functions on the ground.

The central empirical finding is striking in its clarity: collective action works, at least in the short term. Communities, local authorities, business actors, and transnational diaspora networks successfully mobilize resources, finance public works, and support infrastructure delivery through mechanisms that will be familiar to development economists everywhere: matching grants, co-financing arrangements, and participatory planning processes. In practice, this means that when a municipality cannot fund a water system, local businesses contribute capital, diaspora remittances fill the gap, and community members participate in deciding where the infrastructure should go. The result is a patchwork of locally financed public goods that emerges in the spaces where formal state provision is absent or too weak to reach.

This pattern is especially significant in Somalia, where decades of conflict, state collapse, and fragmented authority have produced what scholars call hybrid governance, a system in which formal government institutions, traditional clan structures, market actors, and international organizations all exercise overlapping forms of authority. Much of the existing scholarship on Somalia has catalogued the descriptive features of this hybridity, mapping who governs what and where. Dirir’s contribution is to shift the analytical focus from description to dynamics, asking not just how hybrid governance is structured but how it performs over time when measured against the actual delivery of public goods that citizens need.

Yet the study’s most consequential findings concern what happens after the ribbon-cutting. The research identifies severe long-term sustainability deficits that undermine the durability of collectively financed infrastructure. Lifecycle maintenance constraints mean that wells, roads, and buildings constructed through community mobilization often lack institutional arrangements for ongoing repair and upkeep. Land tenure insecurity creates uncertainty about whether the infrastructure will remain under the control of those who built it. Elite capture allows powerful local actors to redirect the benefits of public goods toward themselves. And structural governance fragmentation, the very feature that makes Somalia’s institutional landscape so fluid, prevents the coordination needed to sustain projects across political transitions and funding cycles.

The study’s most original theoretical contribution is what Dirir calls the state-cooptation paradox. The paradox works like this: subnational collective action effectively addresses immediate public finance gaps, allowing communities to obtain services the state cannot provide, but in doing so it simultaneously perpetuates long-term institutional mandates that properly belong to formal government and generates significant spatial inequities across regions. When communities learn to provide for themselves, the state faces reduced pressure to build its own capacity, and the informal arrangements that fill the gap become entrenched. Collective action, in other words, is both a solution to state weakness and a mechanism that reproduces it.

Compounding this paradox are transnational capital flows, particularly the remittances and investments that flow from Somalia’s vast diaspora. The study finds that these cross-border financial flows allocate resources based on ancestral clan geography rather than need, which inadvertently exacerbates regional spatial inequalities. Diaspora members naturally direct their money toward the regions and communities where their own kin live, meaning that areas with large, prosperous diaspora populations accumulate infrastructure and services while regions with weaker transnational ties fall further behind. The result is a geography of development that mirrors clan settlement patterns, hardening spatial disparities that formal fiscal equalization mechanisms, were they functioning, might otherwise moderate.

These dynamics have implications that extend well beyond Somalia’s borders. Fragile and conflict-affected states around the world, from Afghanistan to South Sudan to Haiti, exhibit similar combinations of weak formal capacity, strong community and diaspora networks, and internationally funded development programs. The Somali case suggests that international donors and development agencies should pay close attention to how their interventions interact with local collective action. Aid architectures that channel resources through community structures may achieve impressive short-term delivery but risk entrenching the very institutional fragmentation that limits long-term development. Conversely, programs that ignore community capacity in favor of building formal state institutions may fail to deliver services at all during the extended period required for state-building.

The study’s conclusion is measured but firm: while collective action effectively generates essential public utilities beyond state boundaries, its long-term sustainability relies entirely on supportive formal institutional frameworks, legal protections, and coordinated governance systems. Community mobilization can build a well, but only legal clarity over land tenure can guarantee that the well remains a public good rather than a private asset. Diaspora capital can finance a school, but only coordinated governance can ensure that teachers are paid, curricula are maintained, and the school serves all children rather than a favored clan. The lesson for policymakers is that collective action and state capacity are not substitutes but complements, each necessary for the other to produce durable development outcomes.

For Somalia itself, the research arrives at a moment of cautious institutional reconstruction, as federal and regional administrations work to rebuild fiscal systems and legal frameworks after decades of fragmentation. The study suggests that the country’s remarkable social capital, expressed through clan solidarity, business networks, and diaspora engagement, represents an asset that formal institutions should harness rather than displace. Whether Somalia’s emerging governance structures can convert the energy of collective action into sustainable, equitable public goods provision, without falling into the state-cooptation trap that the study identifies, may determine whether the next two decades of Somali development look fundamentally different from the last. The open-access study, published on 1 October 2026, provides a detailed evidentiary foundation for that conversation, and its framework for analyzing the lifecycle of community-driven public goods is likely to inform research and policy across the broader landscape of fragile states.

Subject of Research: Collective action and public goods provision under limited state capacity in Somalia

Article Title: Collective action for subnational public goods provision amid limited state capacity in Somalia

Article References: Dirir, M. M. A. (2026). Collective action for subnational public goods provision amid limited state capacity in Somalia. Discover Sustainability. https://doi.org/10.1007/s43621-026-04833-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04833-y

Keywords: collective action, public goods, Somalia, hybrid governance, state capacity, fragile states, diaspora remittances, community-driven development, elite capture, spatial inequality, qualitative document analysis, sustainability

The research, published on 19 February 2026 as volume 3, article 11 of the journal, rests on a structured literature review and conceptual analysis rather than new empirical data. Pesek draws on governance theory and on critical scholarship concerning digitalisation, platformisation, and datafication to build an analytical framework capable of describing what actually happens when AI enters schools. The core insight is that AI behaves as a systemic and transversal actor. Unlike a textbook or a learning management system, it does not sit neatly inside a single layer of the education system. It operates across the boundary between centralised regulation and decentralised educational practice, shaping decisions at the ministry level and in individual classrooms simultaneously, often without either policymakers or teachers fully noticing.

To make this complexity tractable, the paper introduces a conceptual distinction between three layers of educational AI. The first layer consists of foundational AI infrastructures, essentially the large AI models on which everything else depends. The second layer is AI content, the generated material that flows into lessons, assessments, and learning resources. The third layer comprises AI tutors, the interactive systems that increasingly mediate the relationship between learners and knowledge. Pesek argues that these three layers demand different governance responses, because they concentrate power, risk, and accountability in different places. Treating them as a single undifferentiated category of “AI tools,” he suggests, is one of the reasons existing policy frameworks have struggled to keep pace.

The analytical heart of the paper is a reconfigured hybrid governance model. Hybrid governance refers to arrangements in which authority is shared between state regulators, commercial platform providers, local institutions, and professional educators, rather than residing in any single actor. The study shows that AI has reconfigured these hybrids in ways that were not anticipated by earlier digital education policy. When a school adopts an AI tutoring system, for example, decisions about what counts as mastery, how feedback is phrased, and which learning pathways are offered are no longer made solely by curriculum authorities or teachers. They are partly encoded in models trained on data that reflect commercial priorities and statistical patterns far removed from any school’s local context. Governance, in other words, has been partially delegated to infrastructure.

From this analysis, Pesek identifies four key governance risks. The first is the homogenisation of learning processes, in which widely deployed AI systems push diverse classrooms toward similar rhythms, formats, and definitions of success, narrowing the space for pedagogical diversity. The second is intensified surveillance, as AI-mediated platforms continuously capture data on how students read, write, hesitate, and solve problems, extending the datafication of education into its most intimate moments. The third risk is blurred accountability: when an AI system produces a misleading explanation, an unfair assessment, or a harmful recommendation, it is often unclear whether responsibility lies with the developer, the platform, the school, or the teacher. The fourth risk is the erosion of student and teacher agency, as both groups find their decisions increasingly shaped by opaque recommendation engines rather than by professional judgement or learner choice.

These risks are not hypothetical. The paper situates them within a well-documented policy trajectory. International organisations such as the OECD and UNESCO have repeatedly highlighted both the promise and the governance gap of educational technology, from the OECD’s Digital Education Outlook 2023 to UNESCO’s 2021 guidance for policy-makers on AI and education. Critical scholars including Neil Selwyn and Ben Williamson have long warned that the digitalisation of schooling concentrates power in platform companies and reconfigures educational purposes around data and measurement. Pesek’s contribution is to connect these strands into a single governance argument: the problem is not merely that AI may be used badly, but that the structures through which education systems steer themselves are no longer adequate to the technology they now contain.

The proposed response is a reconfigured hybrid governance approach that differentiates responsibilities across system levels and across AI functions. At the level of foundational AI infrastructures, the paper points toward regulatory oversight of the models themselves, including transparency about how they are trained and evaluated. At the level of AI content, accountability mechanisms need to establish who is answerable when generated material is inaccurate, biased, or inappropriate for a given age group. At the level of AI tutors, governance must protect the integrity of the learner-teacher relationship and ensure that interactive systems support, rather than supplant, pedagogical relationships. Crucially, the framework insists that these responsibilities cannot all be discharged centrally; they must be distributed across national regulators, intermediate authorities, school leaders, and classroom professionals in a deliberate and explicit way.

The paper also advances concrete policy recommendations aimed at operationalising this approach. These include regulatory oversight tailored to the three-layer distinction between AI models, AI content, and AI tutors; accountability mechanisms that make responsibility traceable across the chain from developer to classroom; and explicit protection of educational purpose and professional autonomy, so that teachers retain the authority to interpret, adapt, and when necessary refuse AI-mediated recommendations. The underlying principle is that governance should safeguard democratic values and human-centred education while still allowing education systems to harness the genuine benefits of AI, such as personalised support and reduced administrative burden. The alternative, the paper implies, is a drift in which governance defaults to the incentives of platform providers rather than the purposes of public education.

What makes the study distinctive is its refusal to treat AI in education as a purely technical or ethical dilemma to be solved at the level of individual classrooms. By foregrounding governance as the central analytical and policy concern, it reframes the debate: the question is not only whether an AI tool helps students learn, but who holds power over the systems reshaping learning, who answers when those systems fail, and how the distribution of authority can be redesigned deliberately rather than left to market forces. For policy-makers, school leaders, and educators confronting the accelerating arrival of AI in education, the message is that the deepest challenges are structural. The technology has already reconfigured the architecture of educational governance; the task now is to reconfigure it back, with accountability, transparency, and human agency as explicit design goals rather than afterthoughts.

Subject of Research: Governance of artificial intelligence in education systems

Article Title: Rethinking Education Governance in the Age of AI

Article References: Pesek, I. (2026). Rethinking Education Governance in the Age of AI. Frontiers of Digital Education, 3(1), Article 11. https://doi.org/10.1007/s44366-026-0085-z

Image Credits: AI Generated

DOI: 10.1007/s44366-026-0085-z

Keywords: AI in education, education governance, hybrid governance, accountability, datafication, platformisation, AI tutors, surveillance, teacher agency, education policy, EdTech, governance risks