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Record W4401589640 · doi:10.1080/02699206.2024.2387611

Phonological assessment and analysis tools for Polish: Construction and use

2024· article· en· W4401589640 on OpenAlexaff
Paulina Zydorowicz, Barbara May Bernhardt, Ewa Kaptur

Bibliographic record

VenueClinical Linguistics & Phonetics · 2024
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhonologyPsychologyContext (archaeology)LinguisticsIntervention (counseling)Norm (philosophy)Phonological developmentTest (biology)Language developmentCognitive psychologyNatural language processingDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

This contribution presents tools for the assessment of phonological development of Polish-learning children and an initial qualitative evaluation thereof. The tools are consistent with those developed for 16 other languages in a cross-linguistic study of phonological development that is embedded in the framework of constraint-based nonlinear phonology. This theoretical foundation underlies the composition of a Polish word list for elicitation plus a supplementary analysis and intervention planning form (where intervention is warranted). A qualitative pilot study evaluated the tools in terms of adherence to underlying theoretical constructs, coverage of Polish phonology in the developmental context and utility for testing two children, one of whom was characterised by protracted phonological development. Further steps are required to develop the test into a norm-referenced instrument for clinical and research purposes, including quantitative evaluations of the tools' psychometric properties.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.103
GPT teacher head0.454
Teacher spread0.351 · 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.

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
Published2024
Admission routes1
Has abstractyes

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