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Promoting Peer Interaction Skills

2007· article· en· W2084323458 on OpenAlexaff
Luigi Girolametto, Elaine Weitzman

Bibliographic record

VenueTopics in Language Disorders · 2007
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyLanguage developmentProfessional developmentDevelopmental psychologyPeer groupNaturalistic observationPedagogyMedical educationSocial psychologyMedicine

Abstract

fetched live from OpenAlex

This article highlights the importance of peer interactions for pre–school-aged children's social and language development and demonstrates the need for professional development in this area. Learning Language and Loving It™—The Hanen Program® for Early Childhood Educators and Preschool Teachers is a professional development program that is delivered by speech–language pathologists and teaches educators and preschool teachers to use naturalistic environmental arrangements and verbal support strategies to facilitate peer interactions. This article describes the program and summarizes research that indicates that the program effectively improves educators' use of verbal supports for peer interaction. Other outcomes for children in their care included increased interactions with their peers that continued beyond 2 conversational turns. To date, the efficacy of the verbal support strategies used in this in-service program has been investigated only for typically developing children. The program's usefulness in promoting peer interactions with children who have disabilities (e.g., language disorders) is beginning to be explored.

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)0.002
metaresearch head score (Gemma)0.014
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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.019
GPT teacher head0.396
Teacher spread0.377 · 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

Citations32
Published2007
Admission routes1
Has abstractyes

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