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Record W2026307177 · doi:10.1017/s0305000904006816

The strength of children's knowledge of the role of root morphemes in the spelling of derived words

2005· article· en· W2026307177 on OpenAlexaff
S. Hélène Deacon, Peter Bryant

Bibliographic record

VenueJournal of Child Language · 2005
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMorphemeSpellingLinguisticsPsychologyMorphophonologyRoot (linguistics)Phonology

Abstract

fetched live from OpenAlex

The spelling of words in English is governed in part by the morphemes that make them up. This study examines the strength of children's knowledge of the role of root morphemes in spelling, specifically focusing on whether it can withstand interference by phonological changes. A total of 75 children between seven and nine years of age were given the first parts of two-morpheme transparent and opaque derived words (e.g. musical and objection) and one-morpheme control words (e.g. metal and portion). Children used the clues to a significant extent with the two-, but not the one-morpheme words. This effect was consistent across age groups and across both types of derived words. This is evidence that children's understanding of the link between morphemes and spelling is not impeded by changes in the sound of morphemes. These findings have substantial implications for models of spelling development and for educational practice.

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)0.002
metaresearch head score (Gemma)0.014
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.265
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 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

Citations28
Published2005
Admission routes1
Has abstractyes

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