Keywords
knowledge reception
knowledge verification
socio-scientific issues
grounded theory
How to Cite
Abstract
Socio-scientific issues are complex, ill-structured, and open-ended, often lacking definitive solutions. Managing the COVID-19 pandemic required practical decisions that guided interventions to promote health-enhancing behaviors. Effective decision-making in such contexts involves integrating knowledge from diverse sources, yet challenges remain in how knowledge is received and verified during crises. This grounded theory research examined knowledge reception and verification as critical processes in socio-scientific decision-making. Twenty-five informants were purposefully selected for interviews, drawing activities, and field observations. Data collection followed Hennink and Kaiser’s (2022) steps to achieve theoretical saturation, employing code frequency counts, comparative methods, stopping criteria, higher-order groupings, and code meanings. Findings revealed that knowledge reception occurred through auditory and visual senses, including problem-situation knowledge from social media, self-care knowledge from families, political and economic knowledge from local government, experiential knowledge from communities, and conceptual knowledge from schools. Verification of knowledge involved assessing source referents and comparing multiple sources. Received knowledge also triggered emotional responses that influenced decision-making. From these categories, the Theory on Knowledge Reception and Verification in Socio-scientific Decision-Making was developed. While limited by the characteristics of its informants, setting, and the COVID-19 context, the study provides context-specific explanations of decision-making within a rural Filipino community. It highlights how contextual, cultural, and emotional factors shape responses to crises, offering an interdisciplinary framework rarely described by other decision-making theories. Future research may expand this framework by examining how communities in varying contexts receive and verify knowledge, informing localized responses during uncertainty.
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