Methodological Issues in Research on Working Memory and L2 Reading Comprehension
Bibliographic record
Abstract
The relationship between working memory (WM) and second language (L2) reading comprehension has received considerable attention for nearly three decades. Although studies in this line of research generally report a small to moderate relationship between WM and L2 reading comprehension, comparison of studies remains challenging due to the lack of specification of the kind of comprehension under investigation (e.g., textbase, situation model) and the means of comprehension assessment. In addition, inconsistencies in the usage, scoring and analysis of WM measures further complicate the interpretation of findings across studies. Thus, in this chapter, we examine L2 reading-WM studies, paying particular attention to methodological considerations surrounding the use and scoring of WM tasks and the assessment of comprehension. We argue that methodological decisions can have non-trivial effects on this line of research and provide task recommendations based on current theorizing in reading
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".