Scripting with Bodies: How Body Work Facilitates Constructing Collective Identity
Bibliographic record
Abstract
Most literature on collective identity construction in social movements considers the guiding role of either leaders or pre-established actors, leaving largely unexplored the question of how this process in a leaderless distributed movement unfolds. In the few studies on identity formation within uncoordinated movements, attention to the discursive aspects of developing a sense of unity among participants outweighs consideration of the material and relational aspects, especially related to the human body. I address these voids by studying the role of body work in a spontaneous horizontal protest movement centred on women’s bodies in Iran. By examining the visual-discursive, material, and relational dimensions of purposeful and reflexive attempts made by various activists in the process of what I call ‘collective identity symbolic work’, I explore the interplay between two heterogeneous forms of social symbolic work (i.e. body work and affect elicitation work) that emerged as the underlying mechanisms of shaping collective identity. The theoretical model developed in this paper postulates how performative (targeting actual bodies) and formative (targeting mediatised bodies) types of body work practices, when processed through partly virtual interaction rituals arranged by the activists, convert to shared emotional accounts that lead to the fusion of a set of transitory embodied collective identity claims. Thus, by illustrating how ritualised emotions become an integral part of an emergent social structure that transforms corporeality into a sense of cohesion, the model provides a micro-processual explanation of how body work facilitates crafting a sense of solidarity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".