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Record W4253378025 · doi:10.1075/z.95

The Japanese Mental Lexicon

2000· book· en· W4253378025 on OpenAlexaff
Joseph F. Kess, Tadao Miyamoto

Bibliographic record

VenueJohn Benjamins Publishing Company eBooks · 2000
Typebook
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMental lexiconKanjiKanaLinguisticsLexiconAphasiologyPsychologyPsycholinguisticsFocus (optics)CognitionComputer scienceCognitive psychologyAphasiaChinese characters

Abstract

fetched live from OpenAlex

This book surveys the psycholinguistic dimensions of lexical access to the mental lexicon in Japanese, and attempts to synthesize the diversity of Japanese psycholinguistic research into the nature of written word processing in Japanese. Ten chapters focus on the nature of such psycholinguistic inquiry and its history, the structural origins of the Japanese script types and their relative frequencies, lexical access studies in kanji, the hiragana and katakana syllabaries, romaji, and mixed text processing, laterality preferences in kana/kanji processing and their implications for scientific discussions of language and cognition, evidence from eye-movement studies, the acquisition of orthographic skills by Japanese children, and a review of the implications and conclusions that arise from the contributions of such research. The text is directed at filling the need for an overview of this research because of its importance to theoretical modelling in linguistics and psychology, as well as aphasiology, mathematical and statistical linguistics, educational practices and governmental intervention in respect to language policies, and studies of linguistic and cultural history.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.009

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 head0.022
GPT teacher head0.283
Teacher spread0.260 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations32
Published2000
Admission routes1
Has abstractyes

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