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Record W3137113448 · doi:10.26522/brocked.v30i1.829

A promising family literacy project based on male reading models

2021· article· en· W3137113448 on OpenAlexaffvenue
Isabelle Carignan, Robin L. Quick, Annie Roy‐Charland, Marie-Christine Beaudry, Stéphanie Charbonneau

Bibliographic record

VenueBrock Education Journal · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversité du Québec à MontréalUniversité de MonctonUniversité TÉLUQ
Fundersnot available
KeywordsReading (process)Context (archaeology)LiteracyPsychologyPedagogyFocus groupMathematics educationSociologyBiologyLinguistics

Abstract

fetched live from OpenAlex

This article discusses an innovative family literacy project that was implemented in a community setting. Male trios consisting of a male relative, a struggling reader in elementary school and a pre-service teacher were created. The goal was 1) to develop student’s motivation to read by using male reading role models and allowing the student to read what he truly enjoys in a non-school environment and 2) document male reading practices as trios. To document the progression of four male trios, we used a semi-directed interview, a focus group and a logbook. The results of this multiple-case research study showed an improvement regarding the student’s motivation to read in the context of male trios, different reading practices inside the trios and a positive evolution in the relationship between the student and participating male relative has been observed.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.003
Scholarly communication0.0020.002
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.047
GPT teacher head0.295
Teacher spread0.248 · 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 designQualitative
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

Citations1
Published2021
Admission routes2
Has abstractyes

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