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Morphology in Dene Languages

2020· reference-entry· en· W3009143793 on OpenAlexaff
Keren Rice

Bibliographic record

VenueOxford Research Encyclopedia of Linguistics · 2020
Typereference-entry
Languageen
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMorphemeLinguisticsVerbPrefixWord formationNounLexicalizationComputer scienceLexemeAgglutinative languageArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

Abstract Dene languages are often recognized for their morphological complexity. The languages are known in particular for their complex verbal morphology, and the Dene verb word has received considerable attention in the literature. The verb word is polysynthetic, with several unusual properties: the actual morpheme inventory is relatively small, with rich word formation possibilities; it is prefixing, while suffixing is far more common amongst the world’s languages; what is a single morpheme from a semantic perspective can be discontinuous, illustrating what Whorf calls interrupted synthesis; a single morpheme can be both semantically productive and lexically idiosyncratic; some affixes are mobile; there is considerable homophony; fusion of morphemes is common; and aspects of the phonology lead to surface opacity, with unexpected allomorphy. Several proposals have been introduced to account for the structure of the verb word, and psycholinguistic and sociolinguistic factors that enter in to understanding the complexities of the verb word have been addressed. There is also research on the acquisition of and teaching of the verb word. Overall, it is important to ask what the structure of the verb is synchronically, and what, while interesting, is a consequence of diachronic developments. In addition to the well-studied complexities of the verb, there are also interesting aspects of other categories. The nouns are worthy of attention for their formation, a noun classification system, and nominal possession. The directional systems of Dene languages tend to be rich, including both a root that indicates direction and a prefix that specifies distance or direction from the speaker. At least some of he languages also have evidentials, and these are, in general, understudied. Dene languages, like many other languages of North America, are now being learned largely as second languages. This increases the urgency to study areas such as acquisition and language use in order to help in sustaining the languages in communities where this is desired.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.082
GPT teacher head0.357
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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