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Record W2101776640 · doi:10.1017/s0142716403230083

<i>Phonological development in specific contexts: Studies of Chinese-speaking children</i>. Zhu Hua. Cleveden, UK: Multilingual Matters, 2002, Pp. 218.

2003· article· en· W2101776640 on OpenAlexaff
Che Kan Leong

Bibliographic record

VenueApplied Psycholinguistics · 2003
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhonologyPhoneticsLinguisticsPsychologyRepresentation (politics)Phonological developmentContext (archaeology)Phonological ruleMarkednessPerceptionHistoryPhilosophy

Abstract

fetched live from OpenAlex

Phonology is usually explained as the study of speech sounds and their patterns and functions in the lexical representation of speakers of languages (Kenstowicz, 1994; Spencer, 1996). Some years ago the question, “Where's phonology?” was raised by Macken (1992) in the context of the large concern with the phonetics of acquisition and the conception of phonological acquisition as acquisition of phonetics. This division between phonology and phonetics may be traced to the work of the Prague School of Trubetzkoy (1939/1969) and earlier. Macken proposed a relatively autonomous phonological component, with perceptual, articulatory, and phonological-based abstract rules and principles, to account for learners' lexical representation and suggested a hierarchy of prosodic words, segments, and features as the basis of phonological acquisition (Macken, 1979, 1992). Recent emphasis is on the interaction among phonology, phonetics, and psychology, and this integrative approach has implications for studying common crosslinguistic speech sound patterns (Ohala, 1999). Phonology is further seen as addressing the questions of rules and representations, which may apply to “compute the phonetic representation” within the framework of universal grammar (Kenstowicz, 1994, p. 10).

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.373
Teacher spread0.314 · 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.

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

Citations1
Published2003
Admission routes1
Has abstractyes

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