Sound the alarm!: Disrupting sonic resonances of an elementary English language arts classroom
Bibliographic record
Abstract
Classrooms are host to complex sonic ecologies informed by ritualized patterns and routines, but there remains a dearth of scholarship studying everyday sounds of schooling. Such research is important because it can amplify in new ways how children’s identities are constructed and thickened over time. This interpretive case study takes up the question as it interrogates sound’s capacity to inform children’s identities in a resource-limited, public elementary school in the Midwestern United States. Specifically, this inquiry explored in what ways sonic experiences might (re)produce and/or thicken (systemic) identities and positionings for children. Using critical positioning theories, the author details how sonic (re)occurrences informed children’s abilities to know, to be, and to be known in their classroom community. Through listening to the ambient experiences of everyday classrooms, the findings from this study showcase, new possibilities for exploring children’s identities and positionings. Through the storied experiences of two boys—acoustically described and analyzed—the author challenges critical early childhood researchers and educators to hear, perhaps for the first time, “unheard” everyday sounds like the alarm and consider the multiple ways such sounds resonate in classrooms.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.008 |
| 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".