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Record W2769233171 · doi:10.21037/aes.2018.ab104

AB104. Validation of the international reading speed texts in a Canadian sample

2018· article· en· W2769233171 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnnals of Eye Science · 2018
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsCentre Intégré de Santé et de Services Sociaux des LaurentidesConcordia UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de MontréalSanté MontérégieMAB-Mackay Rehabilitation CentreCentre intégré de santé et de services sociaux de la Montérégie-CentreCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
Fundersnot available
KeywordsNormativeReading (process)Sample (material)PsychologyOptometryAudiologyLinguisticsMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

Background: The International Reading Speed Texts (IReST) were developed in Europe as a standardized measure to assess continuous reading in normally sighted and visually impaired individuals. The IReST is used throughout the United States and Canada to assess reading speed; however, the normative values may not be valid in North America (NA). Additionally there are no normative values for individuals with visual impairments. The aim of this study was to validate the IReSTs in a normally sighted English-speaking NA sample with and without a simulated reduction in visual acuity. Methods: Fifty undergraduate students from Concordia University participated in this study. Participants were systematically assigned to a counterbalanced order of testing conditions and were asked to read all 10 IReSTs aloud. The normal and impaired vision conditions were counterbalanced such that the first set of five IReSTs were read with either the participants normal/corrected-to-normal vision or with a simulated 20/80 visual impairment. Results: Multiple two-sample dependent t-tests using a Holm-Bonferroni correction for multiple comparisons were used to compare the IReST values (means and standard deviations) to the current sample; the results showed statistically significant differences between the current samples mean reading speed and the values provided by the IReSTs. In all cases, P were equal to or less than 0.005. Mean difference scores ranged from 14.87 to 30.05 wpm, with 95% confidence intervals ranging from 4.82 to 43.32. Measures of effect size using bias corrected Hedge’s g* ranged from 0.83 to 1.32, with 95% confidence intervals ranging from 0.25 to 1.93. Multiple two-sample dependent t-tests using a Holm-Bonferroni correction for multiple comparisons were used to compare the mean reading speed in wpm of the normal and impaired vision conditions; the results showed statistically significant differences between the mean reading speeds of the normal vision condition and the simulated impairment condition on the IReSTs. In all cases, the P were less than 0.001. Mean difference scores ranged from 25.44 to 41.8 wpm, with 95% confidence intervals ranging from 21.66 to 46. Measures of effect size using bias corrected Hedge’s g* ranged from 2.74 to 3.81, with 95% confidence intervals ranging from 1.97 to 4.74. Further Bayesian analyses revealed BF10 factors ranging from 1.277×107 to 7.334×1011, indicating decisive evidence for the research. Conclusions: There are statistically significant differences in reading speed between the NA English sample and the normative values established by the IReST; such that reading speeds of the NA English sample are slower than the normative values of the IReST. Additionally, participants in the simulated impairment condition read the IReSTs significantly slower than the normal vision condition.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.120
GPT teacher head0.387
Teacher spread0.267 · 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