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Record W2920915859 · doi:10.1002/tesj.445

Read‐alouds in the upper elementary classroom: Developing academic vocabulary

2019· article· en· W2920915859 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTESOL Journal · 2019
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVocabularyMathematics educationLiteracyCurriculumVocabulary developmentBridging (networking)PedagogyPsychologyTeaching methodComputer scienceLinguistics

Abstract

fetched live from OpenAlex

This article highlights the potential of teacher read‐alouds of informational texts for building academic vocabulary. These represent the general, high‐utility words with Greek and Latin roots and the discipline‐specific words associated with increased academic rigor of curriculum in the upper elementary grades. The author provides the theoretical underpinnings and underscores the importance of building and bridging oral academic vocabulary to written academic literacy through a series of linked, scaffolded learning tasks. These tasks provide opportunities for recycling and practice with new words and transforming them to written modes, resulting in deep learning. These ideas are suited for working with preservice teachers in initial teacher preparation programs. In‐service teachers could also use these materials in their classrooms or for professional development in a community of practice setting where collaborative work, discussion, and shared reflection are valuable adjuncts for introducing new teaching ideas.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.027
GPT teacher head0.330
Teacher spread0.303 · 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