ArticleGM crops & food2026
Trust and doubt coexist: an empirical study on the acceptance mechanism of transgenic technology among Chinese youth.
Article in GM crops & food, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
As a scientific issue characterized by both controversy and sensitivity to public risk, genetically modified (GM) technology has become an important entry point for understanding contemporary science communication through its dissemination and acceptance among young people. This study takes 25 Chinese youth aged 19-27 as its research participants, collects data through semi-structured in-depth interviews, and analyzes the process of attitude formation by applying grounded theory through open coding, axial coding, and selective coding. The findings show that young people usually take government announcements, expert interpretations, and mainstream media reports as their initial points of reference, while also conducting cross-source verification through social media, peer discussion, and personal experience, thereby displaying the coexistence of authoritative dependence and rational skepticism. On this basis, respondents did not generally develop attitudes of absolute support or outright rejection, but instead showed a tendency toward limited acceptance with conditional reservations. Further analysis indicates that accumulated socialization experiences and institutional trust give a certain degree of continuity to such judgments in subsequent encounters with information. On this basis, this article proposes an interpretive framework of authoritative dependence - rational skepticism - balance effect - trust inertia. The findings presented here constitute an interpretive understanding of the logic of attitude formation within a specific sample, rather than a population-level generalization.
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