Reifying, Disorienting and Restoring Gender Binaries in Dialogic Literature Discussions
Bibliographic record
Abstract
Abstract Dialogic pedagogy aims to bring multiple voices and perspectives into conversation, to create a classroom environment inclusive of multiple student identities, and to challenge hegemonic approaches to knowledge. As such, it seems particularly well‐suited for interrogating gender binaries and enhancing gender equity. Through micro‐ethnographic discourse analysis of video‐recorded literacy lessons, this study examines how traditional gender categories were reified and/or disrupted in literacy discussions in four Israeli elementary school classrooms experimenting with dialogic pedagogy. We found students and teachers frequently relying upon gender stereotypes in the participant examples they offered and in their interpretations of the story, “Fly, Eagle, Fly,” in class discussions. Originally framed as a parable of transformation and growth, the story unexpectedly provided an avenue to explore topics such as gender, transgenderism, and transsexuality. Sporadic instances arose in the discussion in which students subverted traditional binary gender constructs. These fleeting moments of disorientation underscored dialogic pedagogy's capacity to challenge gender norms. However, students and teachers treated transgenderism as taboo, and the topic's explicit consideration generated anxiety, with the teachers and some of the students trying to silence non‐heteronormative voices. Ultimately, teachers reinforced interpretations that allowed the gender order to be restored and seemed relieved when they were able to move on from the gender trouble episode. The study highlights the potential of dialogic pedagogy to challenge the heterosexual matrix and promote gender equity. However, it also demonstrates the importance of paying greater attention to gender issues in the development of dialogic pedagogy.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".