Reading Rate in L1 Mandarin Chinese and L2 English Across Five Reading Tasks
Bibliographic record
Abstract
This study compared first and second language (L1/L2) reading rate and task performance on five tasks (scanning, skimming, normal reading, learning, memorizing) in two groups of Mandarin speakers (Canada group, China group). A repeated measures ANOVA design was used with one between‐subject factor (Group), two within‐subject factors (Language, Task), and L2 proficiency as a covariate. The results indicated substantial L1/L2 rate gaps for all tasks, but, for the most part, this gap was not the same across tasks. Comparing L1 and L2 task performance, the results indicated some decrease in L2 scores on three tasks (scanning, skimming, memorizing). Regarding group differences, the China group had faster reading rates on two L2 tasks (scanning, skimming) and on all L1 tasks; the Canada group scored higher on the memorizing task, a written recall. L2 proficiency was not a predictor of L2 reading rate but was a predictor of L2 performance on two tasks (learning, memorizing).
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".