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Record W4290672940 · doi:10.1080/01443410.2022.2108767

Direct and indirect effects of cognitive-linguistic and home environment factors on pinyin reading development

2022· article· en· W4290672940 on OpenAlex

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

VenueEducational Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPinyinPhonological awarenessFluencyPsychologyReading (process)VocabularyLiteracyCognitionDevelopmental psychologyLinguisticsChinese charactersMathematics educationPedagogy

Abstract

fetched live from OpenAlex

We examined the developmental relationship between cognitive-linguistic skills (nonverbal IQ, vocabulary, phonological awareness, rapid automatised naming [RAN]), home environment factors (direct teaching, shared book reading, access to literacy resources, parents’ expectations, family’s socioeconomic status [SES]), and pinyin letter knowledge in kindergarten, pinyin reading accuracy at the beginning of Grade 1, and pinyin reading fluency at the middle of Grade 1 in a sample of 159 Chinese children (mean age = 72.70 months). Results showed that phonological awareness, RAN, and direct teaching were associated with pinyin letter knowledge. RAN consistently predicted pinyin reading accuracy and fluency. Moreover, parents’ expectations and family’s SES predicted pinyin reading indirectly through RAN and direct teaching. These findings suggest that the cognitive-linguistic and home environment predictors of pinyin reading are similar to those for Chinese reading, except that vocabulary and access to literacy resources may be less important for pinyin reading.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.325
Teacher spread0.303 · 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