The Detection and Primed Production of Novel Constructions
Bibliographic record
Abstract
Situated within second language (L2) research about the acquisition of morphosyntax, this study investigated English L2 speakers’ detection and primed production of a novel construction with morphological and structural features. We report on two experiments with Thai (n = 69) and Farsi (n = 70) English L2 speakers, respectively, carried out an aural construction learning task that provided low type‐frequency input with the transitive construction in Esperanto—which is marked by accusative case marking (–n) and flexible word order (subject‐verb‐object and object‐verb‐subject)—followed by aural comprehension tests and a priming activity (20 primes and 20 prompts). Results of the aural comprehension tests showed that 23% of the Thai participants (16/69) and 50% of the Farsi participants (35/70) detected the target construction in the input. Results of the primed production task revealed that only those participants who detected the target construction were able to be primed. The findings are discussed in relation to the role of speakers’ previously learned languages in the detection and primed production of novel constructions.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".