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Record W4406639503 · doi:10.1016/j.envsci.2025.103997

Participatory scenario planning: A social learning approach to build systems thinking and trust for sustainable environmental governance

2025· article· en· W4406639503 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Science & Policy · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsDalhousie UniversityBrock UniversityMcGill University
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaFonds de Recherche du Québec-Société et CultureCanada Research ChairsMcGill University
KeywordsCorporate governanceCitizen journalismBusinessEnvironmental governanceProcess managementEnvironmental planningSystems thinkingParticipatory planningSocial learningEnvironmental resource managementKnowledge managementComputer scienceEnvironmental scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Participatory Scenario Planning (PSP), the collaborative process of envisioning plausible futures, is a promising approach to aid environmental management and governance in the Anthropocene. Emerging scholarship on PSP emphasizes its potential for social learning to enhance knowledge, values, and competencies for more sustainable governance. However, empirical evidence that PSP leads to social learning is limited. We explored a PSP exercise for the Bay of Fundy landscape in Nova Scotia, Canada, to assess the degree and durability of three social learning effects among participants (n = 18): changes in systems thinking (cognitive effects), rational (also known as calculative) trust (relational effects), and environmental aspirations (normative effects). We implemented a mixed-methods explanatory design, starting with a quasi-experimental study of the learning effects followed by a qualitative exploration of the influence of composition, process design, and facilitation. Our findings from our case showed that the PSP had multiple positive social learning effects. It enhanced systems thinking by expanding actors’ mental models of which parts of the landscape they perceive to be important for decision-making. It increased rational trust among those involved in the PSP. It shifted environmental aspirations from being outcomes-oriented (e.g., increasing tidal wetlands) toward being process-oriented (e.g., ensuring landscape multifunctionality). These significant learning effects lasted three months after participation in the PSP. Operational attributes, such as the diversity of participants, the activities implemented, and facilitation, were found to heavily influence these social learning effects in different ways. • We explored Participatory Scenario Planning (PSP) as a social learning process. • PSP can influence systems thinking, rational (calculative) trust, and environmental aspirations. • Social learning effects in our case study are durable at least three months after the PSP process. • Diversity of participants, well-designed process, and skilled facilitation are key to catalyzing social learning in PSP. • We provide a useful conceptual framework and methodological approach to examine PSP as a social learning process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.373
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it