Protracted development in the heritage lexicon
Bibliographic record
Abstract
Abstract Research on heritage language acquisition at the school age has shown protracted development and early stabilisation in morphosyntax and the lexicon. Our study examined the properties of resultative verb compound (RVC), a structure at the crossroads of the lexicon and morphosyntax, in second-generation child heritage speakers in the UK who had continuous input in Mandarin Chinese since birth. We analysed three subclasses of RVCs produced by the heritage children ( n = 27, age 4–14) and their parents ( n = 18) in an oral narration task and compared them with those by children in Beijing ( n = 48, age 4–9) from existing databases. Our results show that the heritage children produced RVCs quite frequently and felicitously yet highly repetitively and conservatively, with a remarkably large proportion of their RVCs consisting of a strongly lexicalised subclass with direct lexical equivalents in English. Correlational analyses show that the heritage children’s RVCs improve with age, rather than provision of RVC in the parental input, indicating the role of cumulative input in RVC acquisition. Overall, the development of RVC in heritage Mandarin is delayed rather than stabilised or attrited, supporting the lexical account for grammatical vulnerabilities in proficient heritage speakers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".