A learner corpus analysis: Effects of task complexity, task type, and L1 & L2 similarity on propositional and linguistic complexity
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
Abstract Learner corpora provide researchers with a rich pool of resources that can complement experimental studies. The purpose of the present paper is to provide task complexity researchers, for the first time, with further insight regarding interactive effects of task complexity, task type, task modality, and L1 background on linguistic and propositional complexity. Analyzing 720 intermediate-level (B1) written texts that were extracted from open access online language learning platform, the EF-Cambridge Open Language Database (EFCAMDAT) revealed that there was a significant interaction effect among task design features (task complexity, task type, and L1 background) that influenced linguistic and propositional complexity of written texts. This suggests that task complexity does not function in isolation of other task design features such as task type and L1 background.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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