In the age of information abundance, social and psychological sciences face a profound challenge: interpreting and discussing values, meanings, and knowledge that lie beyond data. This paper proposes an epistemic framework termed the absurdist approach to unveiling possible paradoxical thinking, grounded in the principles of Granular Interaction Thinking Theory (GITT) and enriched by self-reflection through literary and philosophical paradoxes that are exemplified by Wild Wise Weird —a collection of fables that intertwine innovative storytelling with contemporary sensibilities, offering both moral insight and moments of self-reflection. Specifically, Wild Wise Weird illustrates how events of negligible probability can nonetheless possess deep significance, thereby complementing GITT’s explanatory mechanisms by completing the cognitive cycle of interpretation and reflection. Through this synthesis, the absurdist approach encourages intellectual humility in constructing arguments and interpretations, prompting scholars to look beyond data and statistical findings toward the epistemic depths of human reasoning. Ultimately, this combination represents an epistemological application that strengthens methodological practice. It enhances the analytical power of both quantitative and qualitative research while mitigating the risks of overgeneralization—yet still recognizing and valuing low-probability patterns that often carry profound insight across disciplines, including psychology, sociology, healthcare, environmental studies, politics, and economics. • The paper proposes a thinking method that integrates the theoretical reasoning power of GITT with counter-assumptive propositions found in literary and philosophical paradoxes, exemplified by Wild Wise Weird . • This combination enables deeper exploration of humanistic values and the recognition of low-probability patterns often overlooked in socio-psychological sciences. • As an epistemological approach, it enhances both quantitative and qualitative research by expanding interpretive capacity while reducing the risks of overgeneralization.
Nguyen et al. (Wed,) studied this question.