“They're Like Slash”: Multimodality and Embodied Agency in Students' Critical Engagements with Texts
Bibliographic record
Abstract
Abstract Despite recent calls to more fully incorporate multimodal perspectives into literacies research, there is still limited scholarship examining how students critically engage in reading activities by drawing on embodied practices. Racially and linguistically minoritized students are particularly disadvantaged by dominant logocentric and developmentalist approaches, which privilege oral and written discourse and often position these students as less capable of performing complex literacy practices. Drawing from three independent ethnographic studies, our multimodal interactional analysis examines how students of a range of ages and raciolinguistic backgrounds use embodied actions and other semiotic resources to agentively navigate text, task, and ideological constraints in activities involving reading and analyzing texts. Our analysis demonstrates the crucial role of students' embodied practices in expanding upon and challenging the constraints of literacy activities, focusing particularly on how students leveraged epistemic stance‐taking, embodied affective responses, and embodied forms of argumentation to negotiate and co‐construct meaning. Through a focus on embodied agency, this paper presents and applies an interactional perspective on the embodied nature of literacy activities; shows how students' creative mobilizations of embodied and other semiotic resources contribute to their critical readings of texts; and offers pedagogical and methodological implications for ways educators and researchers can attend to the intricacies of students' embodied sense‐making in literacy activities.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".