Depth versus Breadth of Lexical Repertoire: Assessing Their Roles in EFL Students’ Incidental Vocabulary Acquisition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study explores the roles of depth and breadth of lexical repertoire in L2 lexical inferencing success and incidental vocabulary acquisition through reading. Students read a graded reader containing 13 pseudo-words and attempted to infer the meanings of underlined target words. The Word Associates Test (WAT, Read, 2004) and the Vocabulary Levels Test (Schmitt, Schmitt, & Clapham, 2001) were administered to measure depth and breadth of lexical repertoire respectively. To rate retention of inferred meanings, I administered the Vocabulary Knowledge Scale (VKS, Paribakht & Wesche, 1996, 1997) with a repeated measure design. The results indicated that (a) both breadth and depth of lexical knowledge correlated positively with long-term retention of inferred word meanings. However,depth of vocabulary knowledge indicated a higher correlation; and (b) scores on both breadth and depth of vocabulary knowledge had a significant positive correlation with success of lexical inferencing through reading, but depth of vocabularyknowledge was a stronger predictor of inferencing success.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.076 | 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