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Record W2042668256 · doi:10.1177/0142723711427618

First and second graders’ interpretation of Standard American English morphology across varieties of English

2011· article· en· W2042668256 on OpenAlexaff
Tim Beyer, Carla L. Hudson Kam

Bibliographic record

VenueFirst Language · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPluralLinguisticsAmerican EnglishPsychologyMorphemeInterpretation (philosophy)ComprehensionAffect (linguistics)Past tenseNorth American EnglishHistoryCommunicationVerb

Abstract

fetched live from OpenAlex

While African American English (AAE) and Standard American English (SAE) share many features, there are also differences that could affect comprehension. This article examines how 1st and 2nd grade AAE- and SAE-speaking children interpret sentences containing shared lexical and morphological (i.e., plural –s) forms as compared to sentences containing forms that do not regularly occur in AAE (past tense –ed, 3rd person present –s, future contracted –’ll). Using a picture-choice task the study found that while all children correctly interpreted shared forms, only the SAE-speakers, but not the AAE-speakers, successfully interpreted SAE tense morphology. In addition, the AAE-speakers showed no grade-related changes in performance. This suggests that linguistic differences may impact educational access for AAE-speaking students. These, and other implications, are discussed.

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)0.007
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.364
Teacher spread0.336 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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