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Record W4321453148 · doi:10.1075/jhl.22033.col

‘Common nighthawk’ (<i>Chordeiles minor</i>) in Algonquian and Siouan languages

2023· article· en· W4321453148 on OpenAlexaff
Vincent Collette

Bibliographic record

VenueJournal of Historical Linguistics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsLinguisticsIndigenousSimilarity (geometry)Minor (academic)Comparative linguisticsDozenHistoryEthnographyHistorical linguisticsComputer scienceSociologyPhilologyArtificial intelligenceArtPhilosophyBiologyMathematicsArchaeology

Abstract

fetched live from OpenAlex

Abstract Some North American indigenous languages have names for ‘common nighthawk’ ( Chordeiles minor )’, ‘robin’, and ‘bird’ that are strikingly similar phonetically and have served to advocate long-distance genetic relationships among language families. While the Algonquian proto-form for ‘nighthawk’ has a rather straightforward pedigree, this is not the case for Siouan languages. Despite their phonetic resemblance, the ornithonyms for ‘nighthawk’ in half a dozen Siouan languages are unrelated; some are mimetic innovations and others are borrowed. This article analyses how and why ornithonyms are problematic in the application of the comparative method, a reality that affects the validity of long-distance claims, and offers alternative ways to deal with this issue. While ornithonyms can be inherited and undergo all the regular sound changes (or not) like other words, they are also problematic in many respects. First, they can be onomatopoetic and imitate the cry or call of the bird in question – a feature that accounts for their cross-linguistic similarity. Second, they can undergo ad hoc mimetic reshaping or become lexically contaminated based on phonetic similarity with other ornithonyms or words with which they are associated culturally. Third and last, they can be borrowed internally or externally. However, despite these comparative pitfalls (i.e., that some phonetically similar forms in a language family are not cognates), the analysis shows that our understanding of ornithological nomenclature can be enhanced by considering elements of ornithology, mythology, ethnographic knowledge, sayings, and puns pertaining to birds.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.310
Teacher spread0.289 · 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.

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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