MétaCan
Menu
Back to cohort

Psycholinguistic Approaches to Morphology: Theoretical Issues

2016· reference-entry· en· W2523103017 on OpenAlexaff
Christina L. Gagné

Bibliographic record

VenueOxford Research Encyclopedia of Linguistics · 2016
Typereference-entry
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMorphemePsycholinguisticsLinguisticsMorphology (biology)InflectionPriming (agriculture)Cognitive sciencePsychologyCognitionPhonologyComputer scienceNatural language processingArtificial intelligenceCognitive psychologyCommunication

Abstract

fetched live from OpenAlex

Abstract Psycholinguistics is the study of how language is acquired, represented, and used by the human mind; it draws on knowledge about both language and cognitive processes. A central topic of debate in psycholinguistics concerns the balance between storage and processing. This debate is especially evident in research concerning morphology, which is the study of word structure, and several theoretical issues have arisen concerning the question of how (or whether) morphology is represented and what function morphology serves in the processing of complex words. Five theoretical approaches have emerged that differ substantially in the emphasis placed on the role of morphemic representations during the processing of morphologically complex words. The first approach minimizes processing by positing that all words, even morphologically complex ones, are stored and recognized as whole units, without the use of morphemic representations. The second approach posits that words are represented and processed in terms of morphemic units. The third approach is a mixture of the first two approaches and posits that a whole-access route and decomposition route operate in parallel. A fourth approach posits that both whole word representations and morphemic representations are used, and that these two types of information interact. A fifth approach proposes that morphology is not explicitly represented, but rather, emerges from the co-activation of orthographic/phonological representations and semantic representations. These competing approaches have been evaluated using a wide variety of empirical methods examining, for example, morphological priming, the role of constituent and word frequency, and the role of morphemic position. For the most part, the evidence points to the involvement of morphological representations during the processing of complex words. However, the specific way in which these representations are used is not yet fully known.

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)0.002
metaresearch head score (Gemma)0.116
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.116
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
GPT teacher head0.407
Teacher spread0.190 · 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 designNot applicable
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

Citations10
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueOxford Research Encyclopedia of LinguisticsSame topicNeurobiology of Language and BilingualismFrench-language works237,207