Something old, something new: A review of the literature on sleep-related lexicalization of novel words in adults
Bibliographic record
Abstract
Word learning is a crucial aspect of human development that depends on the formation and consolidation of novel memory traces. In this paper, we critically review the behavioural research on sleep-related lexicalization of novel words in healthy young adult speakers. We first describe human memory systems, the processes underlying memory consolidation, then we describe the Complementary Learning Systems account of memory consolidation. We then review behavioural studies focusing on novel word learning and sleep-related lexicalization in monolingual samples, while highlighting their relevance to three main theoretical questions. Finally, we review the few studies that have investigated sleep-related lexicalization in L2 speakers. Overall, while several studies suggest that sleep promotes the gradual transformation of initially labile traces into more stable representations, a growing body of work suggests a rich variety of time-courses for novel word lexicalization. Moreover, there is a need for more work on sleep-related lexicalization patterns in varied populations, such as L2 speakers and bilingual speakers, and more work on individual differences, to fully understand the boundary conditions of this phenomenon.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".