Differential importance of language components in determining secondary school students’ Chinese reading literacy performance
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.
Bibliographic record
Abstract
The present study examined pedagogic components of Chinese reading literacy in a representative sample of 1164 Grades 7, 9 and 11 Chinese students (mean age of 15 years) from 11 secondary schools in Hong Kong with each student tested for about 2.5 hours. Multiple group confirmatory factor analyses showed that across the three grade levels, the eight reading literacy constructs (Essay Writing, Morphological Compounding, Correction of Characters and Words, Segmentation of Text, Text Comprehension, Copying of Characters and Words, Writing to Dictation and Reading Aloud), each subserved by multiple indicators, had differential concurrent prediction of scaled internal school performance in reading and composing. Writing–reading and their interactive effects were foremost in their predictive power, followed by performance in error correction and writing to dictation, morphological compounding, segmenting text and copying with reading aloud playing a negligible role. Our battery of tasks with some refinement could serve as a screening instrument for secondary Chinese students struggling with Chinese reading literacy.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it