Global analysis of social learning's archetypes in natural resource management: understanding pathways of co-creation of knowledge

The paper addresses how social learning (SL) contributes to sustainable natural resource management (NRM) beyond technocratic, hierarchical knowledge-transfer models. It frames knowledge for sustainable NRM as relational and co-created through human–biophysical interactions and emphasizes the rise of learning-based, co-creation approaches in sustainability sciences. However, co-creation can be challenged by coloniality and extractivism dynamics, particularly in Global North–South interactions, underscoring the need for alternative pedagogies (e.g., Freirean praxis) associated with SL. The authors define SL (second school) as collaborative processes that integrate diverse knowledge sources, produce iterative and transformative actions that transcend individuals, and view knowledge as emergent from social interactions. Given diverse uses and meanings of SL across disciplines, there is a need to clarify SL’s forms, functions, and enabling structures based on empirical evidence. The research questions are: What are the archetypical pathways of social learning in NRM? How do they occur in different social and geopolitical contexts? The working hypothesis, informed by cases from Latin America, posits at least two patterns: Endogenous SL—initiated and led within communities, grounded in local rationalities and resources; and Exogenous SL—mediated by external actors and institutions. The study seeks correlations between SL types, geopolitical location (Global North/South), and socioeconomic conditions to surface alternative SL models and their contexts of emergence.

The study employs archetype analysis to identify recurring, non-universal patterns of SL in NRM across heterogeneous cases. Four steps were conducted: (1) Analytical framework development: Synthesizing key SL attributes from prior literature (e.g., materials, processes, actors, methods, resources, outcomes) into three dimensions—geopolitical context, inputs, and outputs—and defining ten analytical categories (e.g., geopolitical location, participants, scope, outcomes, relational capital, methods, financial resources, SL level, natural resources). The “Conflict” category was later excluded due to inconsistent reporting. (2) Case selection: A systematic literature review (PRISMA-guided) of Web of Science and ScienceDirect (search window Sept 20–Dec 20, 2022) using terms combining “social learning” and “natural resource management” with case study variants. From 4,230 initial records (after removing 154 duplicates), title and abstract screening yielded 130 full texts; after quality assessment and methodological consistency checks (excluding non-empirical, game-based SL not comparable), 109 articles were included, comprising 137 individual SL cases. Inclusion criteria required peer-reviewed empirical studies explicitly addressing SL/learning in NRM contexts. (3) Classification/coding: An interdisciplinary team coded each case against the ten categories, with training, inter-rater checks, and resolution via operational definitions and third-reviewer arbitration to ensure consistency. (4) Clustering/archetype generation: Using Python (pandas), Pearson bivariate correlations were computed between SL level (endogenous/exogenous) and other categories. Network graphs (networkx) scaled nodes by correlation strength and colored by sign; cartographic visualization (Pandas/Plotly) mapped archetype occurrence by country. Correlation strengths followed Akoglu (2018). Study limitations acknowledged heterogeneity, scope constraints (NRM-focused, English-indexed, bibliographic databases), and simplifications in the North–South dichotomy.

• Two main SL archetypes emerged: Endogenous and Exogenous. Of 137 cases, 33 were Endogenous, 90 Exogenous, and 14 hybrid/unclear.
• Strong-to-moderate positive correlations characterize archetypes: • Endogenous SL correlates with: learning-by-doing methods; scarcity of financial resources; Global South (notably Latin America); focus on community development; and participation mainly by community individuals. Outputs emphasize strengthened participation, increased critical thinking/reflexivity, and increased environmental knowledge. • Exogenous SL correlates with: availability of financial resources; pre-established methods; Global North (notably Europe); engagement of general stakeholders/institutional representatives; and focus on environmental knowledge and political agreements.
• Geographic patterns: Europe shows higher frequency of Exogenous SL; Latin America shows higher frequency of Endogenous SL. Country-specific signals were not significant.
• Natural resources addressed: Endogenous shows closer correlation with “multiple resources”; Exogenous with “ecosystems.” For many specific resources (e.g., water), proportions were similar across archetypes (e.g., water in 42% of endogenous vs 30% of exogenous cases), yielding non-significant correlations.
• Inputs—financial resources, methods applied, and participant types—exhibited the strongest correlations with SL archetype assignment.
• A subset of 14 cases displayed hybrid or transitioning characteristics between archetypes, suggesting additional subtypes may exist beyond the two main patterns.

Findings support the hypothesis of distinct SL archetypes linked to geopolitical and socioeconomic contexts. Endogenous SL, more prevalent in the Global South (especially Latin America), tends to arise under conditions of resource scarcity, community-led facilitation, and learning-by-doing, aligning with grassroots movements and community development aims. This resonates with theories of stepwise, multi-loop learning where informal networks are central. Exogenous SL predominates in the Global North (particularly Europe), often orchestrated by institutional stakeholders with formalized methods, external funding, and a focus on policy and technical outcomes (environmental knowledge, political agreements). The North–South correlation is not the strongest among variables but indicates a clear trend. The study argues that recognizing Endogenous SL is crucial to avoid overlooking locally grounded processes and to counter tendencies toward coloniality or extractivist dynamics in co-creation. Facilitating communicative action (per Habermas) in Global South contexts may better support deliberation, empowerment, and transformation in NRM. Interfaces are noted between SL processes, endogenous development, and institutional change theories (e.g., distinctions between objective and subjective institutional design), with collaboration serving as a conduit for knowledge co-creation and collective action. The authors caution against dichotomization, recognizing complementarities and the existence of “Souths in the North and Norths in the South,” and recommend further exploration of governance systems, levels of learning, and potential sub-archetypes, including the role of conflict.

The study extends understanding of “what” social learning is by identifying “under which conditions” different SL processes emerge in NRM. It evidences two primary archetypes—Endogenous and Exogenous—showing how inputs (resources, methods, participants) and geopolitical contexts shape outputs (relational capital, knowledge, reflexivity). It highlights alternative and often invisible Endogenous SL models originating in the Global South, where communities may develop innovative, self-constructed knowledge systems addressing intersecting vulnerabilities while managing natural resources. The authors recommend better recognition and support of Endogenous SL as a catalyst for deliberative, sustainable NRM, particularly in the Global South, through transdisciplinary collaboration that values diverse identities and learning models, and intentional engagement with smaller, less-resourced institutions. Future research should examine governance systems, pedagogies, levels of SL, sub-archetypes, and the relationship between conflict and SL.

• High heterogeneity in study methodologies and mixed-method designs reduced cross-case comparability; archetype analysis was chosen to address non-universal patterns.
• Exclusion of certain publication types (books, proceedings, dissertations) and non-English journals due to database focus may bias coverage; some Global South and indigenous/grassroots SL models may be underrepresented.
• The “Conflict” category was excluded due to inconsistent reporting across cases.
• The Global North–South distinction is a simplification and may obscure within-region diversity and evolving geopolitical realities; emerging economies complicate the dichotomy.
• Scope limited to NRM framing; related domains (e.g., climate adaptation, governance) might contain relevant SL cases under different labels (e.g., collective or transformative learning).