Concept Selection and Developmental Effects in Bilingual Speech Production
Why this work is in the frame
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Bibliographic record
Abstract
The present study investigates the locus of language selection in less and more proficient language learners, specifically testing differential predictions of La Heij's (2005) concept selection model (CSM) and Kroll and Stewart's (1994) revised hierarchical model (RHM). Less and more proficient English dominant learners of Spanish participated in a Stroop translation task that included semantically related and unrelated word or picture distracters. The results for the more proficient learners provide support for the CSM as well as the RHM. The results for the less proficient learners provide support for the RHM and demonstrate the continued reliance on lexical level links and the difficulty in accessing the conceptual store during second language production. The selection by proficiency model of bilingual speech production is discussed.
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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 | 0.000 | 0.002 |
| 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