The Micro-Sociology of the Classroom: Group Boundaries, Collective Aggression, and Pedagogical Agency in Student Mobbing
DOI:
https://doi.org/10.54536/ajahs.v5i4.8666Keywords:
Classroom Mobbing, Collective Aggression, Micro-Sociology, Multimodality, Pedagogical Agency, Peer ExclusionAbstract
Student mobbing is examined in this conceptual article as a collective and relational classroom process rather than as a simple accumulation of individual bullying incidents. Drawing on micro-sociology, social semiotics, peer-group research, and scholarship on classroom interaction, the article develops the Classroom Mobbing Multimodal Framework (CMMF). The framework addresses a gap between approaches that explain bullying primarily through individual perpetrator–victim relations and approaches that recognise peer-group processes without systematically integrating the multimodal resources through which exclusion is enacted. CMMF conceptualises collective exclusion through four interconnected dimensions: linguistic, embodied, spatial, and digital. Its analytical premise is that no isolated sign constitutes evidence of mobbing; rather, meaning emerges through recurrence, coordination, sequence, and context. The article also positions pedagogical agency as relational and situated. Teachers are not expected to monitor students continuously or to infer harmful intent from subtle behaviour. Instead, CMMF is proposed as a heuristic for professional reflection, contextual interpretation, documentation, dialogue, and modification of classroom conditions. An illustrative vignette and coding example demonstrate how the four dimensions could be operationalised in future empirical research. The framework is not a validated diagnostic instrument and the article reports no empirical testing. Its contribution is therefore theoretical and methodological: it provides a structured proposition for examining how collective exclusion may emerge across interactional, group, and pedagogical levels and identifies directions for future qualitative, multimodal, and mixed-methods validation.
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