Bibliographic record
Abstract
Working memory (WM) is our limited-capacity storage and processing (memory) system that permeates essential facets of our cognitive life such as arithmetic calculation, logical thinking, decision-making, prospective planning, language comprehension, and production. Since the very inception of WM in the early 1960s (Miller et al., 1960), its role in language acquisition and processing has been extensively investigated both empirically and theoretically by researchers from diverse fields of psychology and linguistics, accumulating an increasingly huge body of literature (e.g., see Baddeley, 2003; Gathercole & Baddeley, 1993 for reviews of early studies). Notwithstanding, the field still lacks a comprehensive and updated profile of conceptualizing and implementing working memory in the broad domains of native and second language acquisition, processing, impairments, and training. In this chapter, we introduce a comprehensive handbook in which key areas of inquiry and practice in working memory and language are at the forefront and theoretical ingenuity and empirical robustness are integrated throughout.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".