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Record W87302166

Exploring the potential of educational television: A review of the literature

2014· review· en· W87302166 on OpenAlexaff
Erin Schryer

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typereview
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsEducational televisionComputer scienceMultimedia
DOInot available

Abstract

fetched live from OpenAlex

For over two decades educational researchers and practitioners have placed tremendous emphasis on ensuring children acquire a solid literacy foundation during the preschool years in order to successfully learn to read once in school (Pelletier, 2008). This focus is predicated on research that suggests children who enter school without a literacy-rich foundation on which to build rarely catch up to their peers who have acquired such a foundation, placing them at risk for a myriad of difficulties across subject areas (Desrochers & Glickman, 2008). The purpose of this systematic aggregative review was to summarize research reporting the effects of educational television viewing – an increasingly prevalent approach to promoting preschoolers’ cognitive development – on preschool viewers’ emergent literacy growth. Review findings may provide a range of educational partners, including early childhood educators, teachers and parents, further information on which to draw when planning activities for more fully supporting children’s early reading development.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0100.010
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.346
GPT teacher head0.567
Teacher spread0.221 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2014
Admission routes1
Has abstractyes

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