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 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 | 0.109 | 0.210 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".