All Together Now: Using Conversational Analysis and Muted Group Theory to Understand Gendered Classroom Discourse in a Cameroonian Primary Classroom
Bibliographic record
Abstract
Using Conversational Analysis (Jefferson, 2004) and Ardener’s (2005) Muted Group Theory, this paper explores classroom data from an African classroom through the sociolinguistic lens of ‘gendered linguistic space’. Emphasis here is on one small village primary school in the rural area surrounding the city of Bamenda, North West, Cameroon and the embodiment of learning displayed by both boys and girls in this learning situation. Reflecting on an African classroom opens up necessary possibilities of understanding what occurs in classroom lessons around the world and ever-new ways of understanding how classroom talk impacts the learning environment in various cultural contexts. In particular, the use of choral responses heavily used in African education challenges current pedagogical ideas concerning classroom talk by offering a less gendered space to engage with learning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".