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Record W1997179884 · doi:10.1017/s0305000906007409

Getting to the root: young writers' sensitivity to the role of root morphemes in the spelling of inflected and derived words

2006· article· en· W1997179884 on OpenAlexaff
S. Hélène Deacon, Peter Bryant

Bibliographic record

VenueJournal of Child Language · 2006
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMorphemeSpellingMorphophonologyLinguisticsOrthographyPsychologyRoot (linguistics)PhonologyReading (process)

Abstract

fetched live from OpenAlex

The English orthography is morphophonemic: spellings encode both morphemes and phonemes. Questions of the starting point and extent of young children's understanding of the link between morphemes and spelling are important for theories of spelling development. We conducted two experiments to address these issues. In Experiment 1, 65 six- to eight-year-old English-speaking children spelled just the first sections of inflected, derived and control words. Their spelling of these first segments was better in inflected and derived words than in control words. The findings were replicated in Experiment 2 with 78 six- to eight-year-old children spelling a greater number of items. These two studies converge on the conclusion that, in specific testing situations, six- to eight-year-old children appreciate the role of root morphemes in the spelling of both inflected and derived words. These results are discussed in relation to current models of spelling development.

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)0.007
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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)0.0020.001

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 head0.004
GPT teacher head0.253
Teacher spread0.248 · 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

Citations75
Published2006
Admission routes1
Has abstractyes

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