Bibliographic record
Abstract
Two nominal internal structures in Mandarin Chinese are introduced in this study, one with the order Demonstrative + Numeral + Classifier + Adjective + Noun, the other with the order Adjective + Demonstrative + Numeral + Classifier + Noun. This study assumes an AgrP between DP and NP (Yoon 1995), and movement of adjectival modifiers from Spec-NP to Spec-AgrP in Mandarin. The 'de' and the pre-'de' segment in the Adjectives undergo a fusion process, incorporating them into a frozen AP, prior to further syntactic operations. The differences between these two options arise from successive AP movement in the latter, which supports Zhang's (2015) generalization. This cyclic movement is triggered by a strong [+foc] feature on the covert head D. This analysis supports a similar approach to left peripheries of CPs and DPs, and also empirically explains the freer position of adjectival modifiers in nominal-internal structures in Mandarin.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".