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Focus in Bantu: verbal morphology and function

2006· article· en· W74215748 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZAS Papers in Linguistics · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBantu languagesFocus (optics)GrammaticalizationMorphemeVerbLinguisticsContrast (vision)HistoryMorphology (biology)Expression (computer science)Computer scienceArtificial intelligencePhilosophyBiology

Abstract

fetched live from OpenAlex

Although verb forms encoding focus were recorded in various Bantu languages during the twentieth century it was not until the late 1970's that they became the centre of serious attention, starting with the work of Hyman and Watters. In the last decade this attention has grown. While focus can be expressed variously, this paper concentrates largely on its morphological, partly on its tonal expression. On the basis of morphological and tonal behaviour, it identifies four blocks of languages, representing less than a third of all Bantu languages: those with metatony, those with a binary constituent contrast between verb ("disjunctive") and post-verbal ("conjunctive") focus, those with a three-way contrast, and those with verb initial /ni-/. Following Güldemann's lead, it is shown there is a fairly widespread grammaticalisation path whereby focus markers may come to encode progressive aspect, then present tense. Many Bantu languages today have a pre-stem morpheme /a/ 'non-past' and it is hypothesized that many of these /a/, which are otherwise hard to explain historically, may derive from an older focus marker.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.597
Threshold uncertainty score0.999

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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