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Record W3175103072 · doi:10.1017/s0305000921000489

Acquisition of variability in Akan Phonology: Labio-palatalized consonants and front rounded vowels

2021· article· en· W3175103072 on OpenAlexaff
Wendy Kwakye Amoako, Joseph Paul Stemberger

Bibliographic record

VenueJournal of Child Language · 2021
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsPhonologyPsychologyLinguisticsPhoneticsFront (military)PhilosophyPhysics

Abstract

fetched live from OpenAlex

This paper addresses how input variability in the adult phonological system is mastered in the output of young children in Akan, a Kwa language spoken in Ghana, involving variability between labio-palatalized consonants and front rounded vowels. The high-frequency variant involves a complex consonant which is expected to be mastered late, while the low-frequency variant involves a front rounded vowel which is expected to be mastered relatively early. Late mastery of complex consonants was confirmed. The high-frequency labiopalatalized-consonant variant was absent at age 3 and not yet mastered even at age 5. All children produced the easier-to-produce low-frequency front-rounded-vowel variant, most at far greater frequency than in adult speech, implying that a child's output limitations can affect which variant the child targets for production. Modular theories, in which phonological plans reflect only the characteristics of adult input, fail to account for our results. Non-modular theories are implicated.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.324
Teacher spread0.313 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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