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Record W4241101442 · doi:10.24124/2010/bpgub685

Cross-linguistic transference of reading skills: Assessing reading difficulties in early French immersion students.

2010· dissertation· en· W4241101442 on OpenAlexaff
Karen L. Andrews

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsCanadian HeritageUniversity of Calgary
Fundersnot available
KeywordsFrench immersionParagraphReading (process)PsychologyLinguisticsReading comprehensionLiteracyComputer scienceMathematics educationPedagogy

Abstract

fetched live from OpenAlex

The purpose of this thesis was to examine both French and English reading errors made by early French immersion students to determine if there was a transfer of literacy skills between the two languages. French immersion students (n = 12) in Grade 2 and Grade 3 were assessed for word reading, word decoding, and paragraph comprehension using standardized English measures and an experimental French assessment tool, the Karen Andrews Reading Assessment Tool (KARAT). The participants, whose first language was English, had not yet received formal English reading instruction. Detailed error analyses revealed that students make the same types of errors when reading in French as when reading in English. Additionally, students who have reading difficulties in one language, experience similar difficulties in the other language. --P. ii.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.376
Teacher spread0.363 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2010
Admission routes1
Has abstractyes

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Same topicSecond Language Acquisition and LearningFrench-language works237,207