Bibliographic record
Abstract
Abstract Starting with the observation that reflexives do not form a homogenous class, we develop a formal typology for reflexives. In particular, on the basis of data from English (Germanic), French (Romance), Shona (Bantu), Plains Cree (Algonquian), and Halkomelem (Salish), we argue for the existence of (at least) five categorically distinct reflexive forms: D‐reflexives, φ‐reflexives, Class‐reflexives,n‐reflexives, and N‐reflexives. We present the following arguments in support of this typology: (i) reflexive forms differ in their syntactic distribution; (ii) reflexive forms differ in the syntactic parallelism they exhibit; (iii) reflexive forms differ in the patterns of multi‐functionality they exhibit; (iv) reflexive forms differ in their syntactic integration into the clause; (v) reflexive forms differ in their semantic mode of composition. The analysis that we develop is couched within the Interface Syntax model of Wiltschko & Déchaine (2010), according to which sound‐meaning bundles freely associate with a universally defined syntactic spine.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".