The Relationship between Depth of Vocabulary Knowledge and L2 Learners' Lexical Inferencing Strategy Use and Success
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Bibliographic record
Abstract
This study examines the relationship between ESL learners' depth of vocabulary knowledge, their lexical inferencing strategy use, and their success in deriving word meaning from context. Participants read a passage containing 10 unknown words and attempted to derive the meanings of the unknown words from context. Introspective think-aloud protocols were used to discover the degree and types of inferencing strategies learners used. The Word-Associate Test (WAT) (Read, 1993) was used to measure the learner's depth of vocabulary knowledge. Results indicate a significant relationship between depth of vocabulary knowledge and the degree and type of strategy use and success. They reveal that (a) those who had stronger depth of vocabulary knowledge used certain strategies more frequently than those who had weaker depth of vocabulary knowledge; (b) the stronger students made more effective use of certain types of lexical inferencing strategies than their weaker counterparts; and (c) depth of vocabulary knowledge made a significant contribution to inferential success over and above the contribution made by the learner's degree of strategy use. These findings provide empirical support for the centrality of depth of vocabulary knowledge in lexical inferencing and the hypothesis that lexical inferencing is a meaning construction process that is significantly influenced by the richness of the learner's pre-existing semantic system.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it