MétaCan
Menu
Back to cohort
Record W4402692541 · doi:10.1080/13504622.2024.2405520

What kind of natural environment picturebooks are young children in China and Korea reading?

2024· article· en· W4402692541 on OpenAlex
Tong Tong Kang, So Hyun Jang

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

VenueEnvironmental Education Research · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Research and Pedagogy
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsEnvironmental educationReading (process)ChinaPicture booksNatural (archaeology)Early childhood educationPedagogyPsychologySociologyGeographyPolitical scienceLiteratureArt

Abstract

fetched live from OpenAlex

This study identified the number of natural environment picturebooks read by young children in Chinese and Korean picturebook libraries and analyzed their content from an ecocritical perspective. The findings indicate that, first, although the number of natural environment picturebooks read by children is higher in Korea than in China, in both countries, these books make up a small proportion of all books read. Second, the covers and endpapers of these picturebooks concisely represent the stories, stimulating children’s curiosity. Additionally, the analysis using the chronotope showed that natural environment picturebooks enabled children to experience changes in time while emotionally empathizing with the protagonists. This study reveals that natural environment picturebooks read by young children in China and Korea provide cognitive and emotional content but lack in actionable content. Therefore, parental, educational, and societal support is necessary to enhance children’s practices in environmental conservation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.468

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.348
Teacher spread0.330 · 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