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Seneca Morphology and Dictionary

2007· article· en· W6932073946 on OpenAlexaboutno aff

Bibliographic record

VenueSmithsonian Digital Repository (Smithsonian Institution) · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsParagraphGrammarNounVerbMorphology (biology)Gerund

Abstract

fetched live from OpenAlex

This work is an extended description of the structure of words in the Seneca language. A description of the grammar of Seneca words has already been published in the International Journal of American Linguistics (Chafe, 1960, 1961 a). A major omission from that work, however, was a comprehensive list of the verb roots, noun roots, and particles of the language, with specification of their grammatical peculiarities and examples of their use. The present work is designed to fill that gap. Its chief purpose is to make available a Seneca dictionary, or lexicon. Since, however, the dictionary contains many references to paragraphs in the Seneca Morphology mentioned above, it was thought useful to republish that work as part of this volume. Republication seems all the more useful in view of the fact that the original Seneca Morphology is scattered through eight numbers of two different volumes of the journal. Minor revisions and corrections have been made, but extensive changes, however desirable they might have been, were out of the question because the references in the dictionary were already keyed to paragraph numbers in the original version, as were the references given in the Grammatical Commentary of Seneca Thanksgiving Rituals (Chafe, 1961 b). Seneca is at present the native language of a few thousand persons, most of whom live on the Allegany, Cattaraugus, and Tonawanda Reservations in western New York State and on the Grand River Reserve in Ontario, Canada. There are few if any speakers now under 30 years of age. Seneca is historically important as the language of the Five (now Six) Nations of the Iroquois and as the language of Handsome Lake, the Iroquois prophet (Parker, 1913; for a history of the Seneca see Parker, 1926). Within the Iroquoian language family, Seneca is a member of the Northern Iroquoian subgroup, which includes also Cayuga, Onondaga, Oneida, Mohawk, and Tuscarora among the languages still spoken. Seneca is most closely related to Cayuga, but the two are different enough to be considered separate languages. The dialect differentiation within Seneca itself is minor. Earlier works on Seneca include several brief grammatical sketches (Voegelin and Preston, 1949, and Holmer, 1952, 1953, 1954) and texts (Hewitt, 1903, 1918). A list of still earlier sources is available in Pilling (1888). The material on which this work is based was obtained during four summers of fieldwork, 1956-59, on the three New York reservations. It consists of an extensive corpus of Seneca words and texts, including formal speeches, legends, historical accounts, and conversations. I am deeply grateful for the assistance provided by numerous speakers of Seneca, above all by Solon Jones and Leroy Button of the Cattaraugus Reservation, Lena P. Snow, Tessie Snow, and Edward Curry of the Allegany Reservation, and Corbett Sundown and Betsy Carpenter of the Tonawanda Reservation. Appreciation is also due to William N. Fenton, Floyd G. Lounsbury, the Smithsonian Institution, Yale University, and especially to the New York State Museum and Science Service, under whose auspices the fieldwork was conducted. Both the Smithsonian Institution and the University of California provided support for the completion of the manuscript, and thanks are due to Karlena Glemser, Myra Rothenberg, and Aura Cuevas for their help in this regard. The lexicon of a language is a vast terrain which no one could hope to explore fully during a few scattered field trips. Although grammatical analysis can perhaps lead to a point of diminishing returns after a reasonable period of investigation, I doubt that such a point has even been approached for the vocabularies of any languages except those few which have a long tradition of lexicography. Certainly the experience which I and others have had with American Indian languages refutes the ethnocentric myth that such languages are poor in their means of expression. What is given in the dictionary of this work is simply what I was able to obtain in a period that was totally inadequate for the purpose. In m

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.196
Threshold uncertainty score0.656

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.011
Science and technology studies0.0040.002
Scholarly communication0.0050.006
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1960.086

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 head0.006
GPT teacher head0.203
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2007
Admission routes1
Has abstractyes

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