Joyful noise and abatement: idle chatter and the undercommons of oracy education
Bibliographic record
Abstract
Abstract This paper imagines oracy education as a reaching‐out for connection with the irreducible socialities of black study. In the wake of imperialist functions of literacy, classroom talk has been left to defend its value against traditionalist views which rebuke, as one UK education minister put it, “idle chatter in class.” We argue that oracy education risks doubling down on the value system outlined by this rebuke – and the white settler‐colonial onto/auto‐epistemology mobilised therein – if it measures the value of talk within this purview. We follow the undercommons of black study and the poetics of relation toward revaluations of idle chatter and noise as modes of thought. We explore the abundant participations of noise beyond the colonial errand of abatement, and we elaborate the relational stakes that idle chatter may invent. We reorient the stakes of the learning conversation with its single guiding lesson into the vibrant jazz riff of a learning cacophony that leaves the continuous echo of possible lessons behind it, proposing new ways of valuing oracy education and new possibilities for participation. Our chatty inquiry practices this ethics, overlapping our shared classroom experiences with discussions of theory and our discussions of theory with yet new possible experiences.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.053 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".