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Record W2284212476 · doi:10.1080/03004430.2015.1131157

Using latent-class analysis to examine the influence of kindergarten children's perspectives of school on literacy and self-regulation outcomes

2016· article· en· W2284212476 on OpenAlex
Kristy Timmons, Janette Pelletier

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

VenueEarly Child Development and Care · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Toronto
FundersOffice of International Science and Engineering
KeywordsPsychologyDevelopmental psychologyLiteracyLatent class modelReading (process)Class (philosophy)Academic achievementMathematics educationPedagogy

Abstract

fetched live from OpenAlex

In this study, we explored the influence of kindergarten children's perspectives of school on their literacy and self-regulation outcomes. Children's early perspectives were captured in a three-question, finger-puppet interview. Responses to the interview questions were coded thematically as being academic and/or social in nature, and were analysed using latent-class analysis. Once children's responses were characterized into classes, further analyses were conducted to understand the application of these perspectives to direct assessments of early reading and writing and self-regulation abilities. Children with less clear perspectives, who mixed academic and social responses, had the lowest performance on all academic measures. Findings add to the existing literature while offering an innovative analytic strategy for examining relationships between children's perspectives and kindergarten outcomes.

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)0.000
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 score0.191
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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