LexKO: A quick, reliable lexical test of Korean language proficiency
Bibliographic record
Abstract
To facilitate objective measures of proficiency for language users of diverse backgrounds, recent research in second language acquisition and multilingualism has developed short, yet reliable, tests of lexical knowledge in a wide range of languages. In this paper, we describe the development of LexKO, a brief lexically based test of Korean language proficiency, including its underlying logic, composition, intended use, and limitations. Three rounds of pilot and validation testing with first- and second-language Korean users resulted in a highly reliable Korean test comprising 60 items that can be completed in a few minutes. Freely available for other researchers to use, LexKO produces scores that correlate significantly with both first- and second-language Korean users' scores on a standardized proficiency test (an abridged version of the Test of Proficiency in Korean) and may thus be helpful in multi-part studies for obtaining a quick, valid measure of proficiency in Korean, one of the world's fastest-growing foreign languages.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".