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Record W4395077771 · doi:10.1177/01427237241245500

Evaluating English-language morphological awareness assessments

2024· article· en· W4395077771 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFirst Language · 2024
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReading comprehensionReading (process)ComprehensionSet (abstract data type)PsychologyLinguisticsComputer scienceCognitive psychology

Abstract

fetched live from OpenAlex

Many studies have shown that morphological knowledge has effects on reading comprehension separate from other aspects of language knowledge. This has implications for reading instruction and assessment: it suggests that children could have reading comprehension difficulties that are due to a lack of morphological knowledge, and thus, that explicit instruction of morphology might be helpful for them, indeed for all children. To find children who might especially benefit from specific instruction in morphology, we would need good tests of morphological knowledge. We evaluated a set of morphological awareness assessments to determine whether they conclusively tapped into morphological knowledge, and found that it was not possible to be certain that they were accurately targeting morphological knowledge.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.058
GPT teacher head0.440
Teacher spread0.382 · 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