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Record W2015582919 · doi:10.1080/00131910500149416

Gender gaps in group listening and speaking: issues in social constructivist approaches to teaching and learning

2005· article· en· W2015582919 on OpenAlexaffabout
Darryl Hunter, Trevor J. Gambell, Bikkar S. Randhawa

Bibliographic record

VenueEducational Review · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
Fundersnot available
KeywordsActive listeningPsychologyCurriculumSocial constructivismConstructivist teaching methodsLiteracyPedagogyCentralityMathematics educationTeaching method

Abstract

fetched live from OpenAlex

Because of its centrality to school success, social status, and workplace effectiveness, oral and aural skills development has been increasingly emphasized in Canadian curricula, classrooms and, very recently, large‐scale assessment. The corresponding emphasis on group processes and collaborative learning has aimed to address equity issues in schools. However, a 1998 Canadian assessment of students' speech communication skills ( N = 551 groups) yielded many significant gender differences in individual listening skills, group production, and self‐efficacy. The oral production in small groups of majority‐ or all‐male groups lagged significantly behind that of all‐female groups. The girl–boy gaps in oracy parallel those evident for literacy in provincial (state), national and international studies among adolescents. Implications are drawn for social constructivist pedagogy, for curricular, instructional, and evaluation practices, and for redressing gender differences.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.172
metaresearch head score (Gemma)0.139
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.172
Threshold uncertainty score0.909

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1720.139
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.006
Science and technology studies0.0070.041
Scholarly communication0.0120.014
Open science0.0050.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.130
GPT teacher head0.333
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2005
Admission routes2
Has abstractyes

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