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Record W2610651153 · doi:10.5617/osla.4420

Negation in Hamar

2017· article· en· W2610651153 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOslo Studies in Language · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsnot available
Fundersnot available
KeywordsNegationLinguisticsMorphemeAgreementInterrogativeSubject (documents)PsychologyMathematicsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This study deals with the negation of declarative and interrogative main clauses, imperatives, and non-verbal and existential sentences in Hamar, an Aroid language of the Omotic language family. It describes the ways in which negation is expressed in the language, and positions the discussion in light of cross-linguistic observations made by Dahl (1979, 2010), Payne (1985), Miestamo (2005, 2007), Eriksen (2011) and others. The morpheme -t- is used in Hamar to mark negation in both verbal and non-verbal clauses. This means that Hamar has a morphological or affixal negation (Dahl 2010). The language uses two different sets of subject agreement affixes for the affirmative and negative counterparts. While affirmative sentences employ a shortened pronoun, a set of agreement suffixes is used in the negative. In this study, it is suggested that the negative verbs may have preserved older subject agreement morphemes which are now lost in the affirmative, as negatives are less affected by innovation, cf. Zargulla in Azeb 2009 and Canadian French in Poplack 2001. Moreover, close interaction is reported between negation and TAM (Tense, Aspect and Mood) categories. For example, some of the aspect/tense categories that occur in the affirmative are neutralised in the negative. Negative constructions in Hamar are not only different from their affirmative counterparts due to the presence of the negation morpheme –t-, but also in terms of subject agreement marking and tense/aspect categories. As a result, it is argued that Hamar has an asymmetric negation system, cf. Miestamo 2005.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.060
GPT teacher head0.328
Teacher spread0.267 · 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