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Record W2090413150 · doi:10.1080/01690960802201010

Morphological effects in auditory word recognition: Evidence from Danish

2008· article· en· W2090413150 on OpenAlexaff
Laura Winther Balling, R. Harald Baayen

Bibliographic record

VenueLanguage and Cognitive Processes · 2008
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSuffixWord (group theory)Word recognitionLexical decision taskDanishComputer sciencePoint (geometry)ComprehensionUniquenessPsychologyWord processingWord lists by frequencyNatural language processingLexical accessSpeech recognitionLinguisticsCommunicationArtificial intelligenceCognitionMathematicsSentenceReading (process)

Abstract

fetched live from OpenAlex

In this study, we investigate the processing of morphologically complex words in Danish using auditory lexical decision. We document a second critical point in auditory comprehension in addition to the Uniqueness Point (UP), namely the point at which competing morphological continuation forms of the base cease to be compatible with the input, henceforth the Complex Uniqueness Point (CUP). Suffixed words with later CUP elicited longer response latencies. We also observed an interaction between suffix frequency and whole-word frequency. Both suffix and whole-word frequency were facilitatory, except for words for which both frequencies are high. For such words, we observed inhibition, and most clearly so for female compared with male participants. Finally, a comparison of complex with simple words revealed that, other things being equal, complex words have a processing advantage compared to simple words. We discuss the consequences of these findings for models of morphological processing.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.306
Teacher spread0.273 · 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

Citations81
Published2008
Admission routes1
Has abstractyes

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