How does language distance affect reading fluency and comprehension in English as second language?
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
Abstract Acquisition of reading skill in a second language (L2) requires development and coordinated use of multiple component skills. This acquisition is less effortful the more similar the first language (L1) of the L2 learner is to that L2. While ways to quantify the L1–L2 distance are well defined in the current literature, the theoretical status of this distance in models of L2 reading acquisition is under-specified. This paper tests whether the L1–L2 distance influences English reading fluency and comprehension directly, via the mediation of component skills of reading, or both. We used text reading data and tests of component skills of English reading from the Multilingual Eye-movement Corpus database, representing advanced L2 readers of English from 18 distinct language backgrounds. Mediation analyses show that the L1–L2 distance has both a direct and an indirect effect on English reading fluency and eye movements, yet it has no effect on reading comprehension. These findings are novel in that they specify the mechanism through which the L1–L2 distance affects L2 reading acquisition.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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