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April 11, 20260 citationsOpen Access

A Methodological Framework for Analysing Stakeholder Perspectives and Policy Formulation in the Gambian Genetically Modified Crops Discourse

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MCMariama CeesayFJFatou JallowLSLamin Sanyang

Key Points

  • The research aims to develop a systematic framework for analyzing stakeholder perspectives and power dynamics in the GM crops policy formulation process.
  • Integrates Q-methodology for understanding stakeholder subjectivity.
  • Utilizes discourse network analysis to map policy coalition structures.
  • Quantifies stakeholder salience using a modified power-interest grid.
  • Assesses evidence influence on policy stances through Bayesian logistic regression.
  • Generates outputs such as discourse cohesion within advocacy coalitions.
  • Quantifies the influence of different evidence types on policy preferences.
  • Reveals distinct proponent and skeptic coalitions with internal agreement scores over 0.7.

Abstract

"background": "The debate surrounding the introduction of genetically modified (GM) crops in African nations involves complex, multi-scalar stakeholder interactions and contested evidence. The Gambia presents a critical case where agricultural policy intersects with food security, biosafety concerns, and international trade dependencies, yet a systematic methodology to deconstruct this discourse is lacking. ", "purpose and objectives": "This article presents a novel methodological framework designed to systematically analyse stakeholder perspectives, power dynamics, and evidence utilisation within the GM crops policy formulation process in The Gambia. The objective is to provide a replicable tool for interdisciplinary policy analysis in similar contested agricultural innovation contexts. ", "methodology": "The framework integrates Q-methodology for modelling stakeholder subjectivity with discourse network analysis (DNA) to map policy coalition structures. Stakeholder salience is quantified using a modified power-interest grid, and the influence of different evidence types on policy positions is assessed via a Bayesian logistic regression model: \\ ({1-p\) = \0 + \1 Ei + \2 Sj, where p is the probability of a pro-GM policy stance, Ei represents evidence type, and Sⱼ denotes stakeholder category. Robust standard errors are employed to account for clustered stakeholder affiliations. ", "findings": "As a methodology article, this section outlines the framework's analytical outputs rather than empirical results. The integrated model generates specific outputs, such as the proportion of discourse cohesion within identified advocacy coalitions and the direction and magnitude of influence exerted by different evidence types (e. g. , peer-reviewed studies versus local experiential knowledge) on policy preferences. A key illustrative output is the quantification of stakeholder alignment, revealing distinct proponent and sceptic coalitions with internal agreement scores exceeding 0. 7. ", "conclusion": "The proposed framework offers a rigorous, structured approach for interdisciplinary research into highly polarised agricultural policy debates. It moves beyond descriptive analysis by quantifying relationships between stakeholder attributes, evidence bases, and policy outcomes, thereby

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Cite This Study

Ceesay et al. (2026) studied this question.

synapsesocial.com/papers/69d9e67a78050d08c1b76dfdhttps://doi.org/10.5281/zenodo.19486209
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