Ultimate attainment in the use of collocations among heritage speakers of Turkish in Germany and Turkish–German returnees
Bibliographic record
Abstract
In this paper we show that heritage speakers and returnees are fundamentally different from the majority of adult second language learners with respect to their use of collocations (Laufer & Waldman, 2011). We compare the use of lexical collocations involvingyap- “do” andet- “do” among heritage speakers of Turkish in Germany (n = 45) with those found among Turkish returnees (n = 65) and Turkish monolinguals (n = 69). Language use by returnees is an understudied resource although this group can provide crucial insights into the specific language ability of heritage speakers. Results show that returnees who had been back for one year avoid collocations withyap- and use some hypercorrect forms inet-, whilst returnees who had been back for seven years at the time of recording produce collocations that are quantitatively and qualitatively similar to those of monolingual speakers of Turkish. We discuss implications for theories of ultimate attainment and incomplete acquisition in 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".