First Language Test Bias? Comparing French-Speaking and Polish-Speaking Participants’ Performance on the Peabody Picture Vocabulary Test
Why this work is in the frame
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Bibliographic record
Abstract
Cognates are known to facilitate second language acquisition and use, as learners tend to assign to a new L2 word the meaning of a similar L1 word. Consequently, for L2 tests that rely largely on lexical items, performance may prove inflated for examinees whose L1 shares many cognates with the language being tested. This article examines the possibility of L1 bias on the Peabody Picture Vocabulary Test (PPVT), a well-established measure of receptive vocabulary knowledge in English. To investigate if performance on the PPVT is affected by cognates, we tested 293 speakers of French and 150 speakers of Polish, since those two languages differ markedly in the number of cognates they share with English. After demonstrating that both groups yield clearly distinct response patterns, descriptive and multivariate statistics confirmed that cognate items enhance test performance: the items with the highest score difference in favour of a language group overwhelmingly consist of cognates for that group only. Mantel-Haenszel and logistic regression show that items that are cognates for one of the two groups are more likely to show differential item functioning than the average items. The results suggest that scores on L2 vocabulary-based tests could be biased by the presence of cognates with the examinee’s first language.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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