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Record W4307994652 · doi:10.1177/15345084221133559

A Comparison of Reading Screeners in Kindergarten: The Texas Primary Reading Inventory and Acadience Reading With English Learners and Monolingual English Speakers

2022· article· en· W4307994652 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

VenueAssessment for Effective Intervention · 2022
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReading (process)PsychologyWoodcockMathematics educationLinguistics

Abstract

fetched live from OpenAlex

Measuring and identifying risk for reading difficulties at the kindergarten level is necessary for providing intervention as early as possible. The purpose of this study was to examine concurrent validity evidence of two kindergarten reading screeners, Acadience Reading and Texas Primary Reading Inventory (TPRI), as well as diagnostic accuracy at different performance levels on the Woodcock-Johnson IV (WJ IV) Reading Cluster and across ( N = 96) emergent bilingual and monolingual English learners in kindergarten. Findings indicated moderate correlations between Acadience Reading and TPRI with the WJ IV. Diagnostic accuracy results showed screening measures were inadequate when predicting WJ IV performance above 90 SS (standard score), but results improved for almost all measures and student groups when the threshold for performance was lowered to 80 SS. Acadience Reading Below Benchmark (AR BB) offered the lowest overall accuracy for emerging bilingual (EB) students. Implications for efficient and accurate use of reading screeners in schools 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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.805

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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.354
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