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Noisy zones of proximal development: Conversation in noisy classrooms

2011· article· en· W1941906044 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Sociolinguistics · 2011
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsConversationContext (archaeology)Perspective (graphical)PsychologyLinguisticsNoise (video)Conversation analysisComputer scienceCommunicationArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

Despite the importance of context in studies of language use, sociolinguists have ignored the impact of noise on conversational interaction. This inattention is of particular concern in classrooms where language is a learning tool. Our research on interaction in noisy settings took place in English language elementary school classrooms with students in grades 3, 5, and 7, whose first language was English. Students were observed during regular classroom activities. Employing a novel method, in which students wore ear‐level microphones, we obtained stereophonic recordings of the noise and conversation that reached each listener's ears. A dosimeter measured the noise levels in each classroom. Analyses of students’ patterns of conversation suggest that noise levels impeded the intended development of complex conversational interaction and collaborative learning. This study also questions the place of acoustics in understanding context, and the significance of the hearer's perspective in sociolinguistic studies of conversational interactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.099
GPT teacher head0.327
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it