Bibliographic record
Abstract
Abstract The inverse morphology of the Algonquian languages has attracted much attention in typological and theoretical linguistics. This book, which is intended as a definitive reference for the Algonquian inverse, describes the patterning of inverse morphology across the Algonquian family and presents a framework for understanding the structure and function of the Algonquian inverse that is empirically driven and typologically grounded. Comprehensive in scope, the book presents data from all documented Algonquian languages and considers not only the morphology of the inverse construction but also its syntax and pragmatics, giving equal weight to diachronic, typological, functional, and formal perspectives. From the integration of these perspectives, a simple and coherent understanding of the nature of the inverse emerges. The key proposal is that the inverse is “deep” in some contexts and “shallow” in others. In interactions between two third persons, the inverse is a “deep” patient voice construction that inverts the canonical morphology, syntax, and pragmatics of a transitive clause. In interactions between a third person and a first or second person, the inverse is a “shallow” hierarchical agreement pattern implemented through a spurious use of patient voice morphology, inverting the canonical morphology of a transitive clause but having no effect on syntax or pragmatics. This split analysis, which reflects the likely diachronic development of the Algonquian inverse, is argued to have various benefits, including the resolution of a longstanding controversy over the syntactic status of the inverse.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".