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Record W4391975132 · doi:10.4314/gjl.v12i2.1

Sociophonetics of [r] in Akan

2023· article· en· W4391975132 on OpenAlexaff
Bernard Boakye, Rebecca Akpanglo-Nartey, Evershed Kwasi Amuzu

Bibliographic record

VenueGhana Journal of Linguistics · 2023
Typearticle
Languageen
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGeology

Abstract

fetched live from OpenAlex

The study interrogates what has hitherto been called ‘free variation’ in Akan (cf. Schachter and Fromkin (1968), Dolphyne (1988), and Abakah (2004)), i.e., the alternation of [r], [l] and [d] in intervocalic position (V_V) and the alternation of [r] and [l] at the second consonant (C2) position of a CCV syllable structure in various dialects of the language. The study follows the quantitative sociolinguistic approach pioneered by Labov (1966) to investigate the extent to which the choice of one rather than the other of these sounds is not free but is dependent on the social backgrounds of speakers (described in terms of their age, gender, educational background and what dialect of Akan they speak). Interview and picture elicitation were the primary instruments of collecting data from 120 respondents (60 speakers of Asante and Fante respectively). The study did not uncover any major dialectal difference in the alternation between [r] and [l] but finds that [d] is decidedly an Asante variant that competes with the other two sounds in the speech of adults. The data however shows that the social variables age, level of education, and gender do influence the choice of [r] versus [l] in both Asante and Fante. Young, educated speakers, especially female speakers, demonstrated a higher tendency of using the [r] variant, which seems to have emerged as the most prestigious of the three variants.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.018
GPT teacher head0.277
Teacher spread0.259 · 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 designObservational
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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Same venueGhana Journal of LinguisticsSame topicLinguistic Studies and Language AcquisitionFrench-language works237,207