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Record W140700934 · doi:10.1177/0145482x1210600105

Reading Speed of Contracted French Braille

2012· article· en· W140700934 on OpenAlexaffabout
Louise Laroche, Jacinthe Boulé, Walter Wittich

Bibliographic record

VenueJournal of Visual Impairment & Blindness · 2012
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversité de MontréalMAB-Mackay Rehabilitation Centre
Fundersnot available
KeywordsBrailleReading (process)Reading rateBlindnessComputer sciencePsychologyLinguisticsOptometryMedicineReading comprehensionPhilosophyOperating system

Abstract

fetched live from OpenAlex

Reading is essential in the context of education. For individuals who do not have easy access to print materials because they are visually impaired (that is, they are blind or have low vision), this process of acquiring knowledge through reading requires additional effort and accommodations. One key adjustment that is made for students for whom is the preferred communication method (hereafter referred to as braille readers) for completing their examinations is the allocation of additional time. Depending on the country, educational system, or institution, the amount of extra time that is may vary; however, in Quebec, Canada, the Ministry of Education, Leisure and Sport (MELS) has regulated the additional time allocated for readers by limiting the extension of the duration of the test to a maximum additional time equivalent of one third the time normally allotted (Gouvernement du Quebec, 2007, chap. 5, p. 55). It has been our experience that this allotment of time is not sufficient to allow students who are visually impaired to operate under the same time constraints as their sighted peers. To propose a concrete change in the amount of time, however, empirical data were necessary. The most easily measured component of an examination that is conducted using is reading speed, often recorded in words per minute (wpm). There are considerable individual differences in reading speed for both print and readers. Legge, Madison, and Mansfield (1999) used both the print and versions of the MNRead test to compare the reading speeds of sighted print readers and readers while reading out loud. Whereas print readers ranged in speed from 150 to 310 wpm (median = 251 wpm), readers ranged from 24 to 232 wpm (median = 124 wpm), indicating that some of the fast readers actually outperformed some of the slower print readers. Still, the median speed was approximately twice as fast for the print readers. These data would indicate that as far as reading is concerned, the time allotment for readers should be twice the time allocated for print readers. This logic does not hold, however, because most students do not take examinations orally. Therefore, a comparison of reading speeds for print and readers was necessary to investigate the difference in reading speed when reading silently. An additional aspect that makes a comparison of reading speeds difficult is the level of in which the text is written (contracted versus uncontracted) and in which language the text is transcribed. Specifically, the language is of importance in contracted because the demands on the reader differ across languages. A reader of English has to learn uncontracted as well as 189 contractions and short-form words to decode text in contracted (Braille Authority of North America, 2008). In comparison, because of differences in the French alphabet and language structure, a reader of French has to learn 1,168 contractions, divided into four levels in Qurbec, to be able to decode a text in contracted (braille abrege) (Gouvernement du Qurbec, 1997). This considerable difference in the complexity of contracted indicates that the cognitive load for readers of French is substantially higher that that of readers of English braille; however, these differences are not reflected in accommodations for students who use French during examinations. Furthermore, a student's reading speed in can be influenced by the reading technique that the student uses. It is now generally accepted that the majority of efficient and fast readers adopt a two-handed scissors pattern, whereby the left reading finger reads to the center of a line, at which point the right takes over and the left is free to find the beginning of the next line (Wright, Wormsley, & Kamei-Hannan, 2009). …

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 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)0.001
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 score0.007
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.048
GPT teacher head0.359
Teacher spread0.311 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations11
Published2012
Admission routes2
Has abstractyes

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