Navajo in the typology of internally-headed relatives
Bibliographic record
Abstract
This paper considers the semantics of Navajo internally-headed relative clauses (IHRCs) with quantified heads. The results of storyboard-based fieldwork show that when the quantifier ’ałníí’dóó ‘half’ occurs in RC-internal position, it necessarily takes RC-internal scope. This result suggests that Navajo IHRCs are amenable to analyses given to Japanese IHRCs (Hoshi 1995; Shimoyama 1999) but challenges claims by Faltz (1995) and Grosu (2012), who argue that t’áá ’ałtso ‘all’ invariably takes RC-external scope. We show that while IHRCs with t’áá ’ałtso do not have precisely the truth conditions expected for EHRCs, their truth conditions differ from what might be expected given a Shimoyama-style IHRC analysis (pace Grosu 2012). However, we consider one way to explain this behavior while maintaining surface scope for all Navajo quantifiers.
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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 | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".