MétaCan
Menu
Back to cohort
Record W3106147158 · doi:10.1080/15391523.2020.1809034

#Digital parents: Intergenerational learning through a digital literacy workshop

2020· article· en· W3106147158 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

VenueJournal of Research on Technology in Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of British ColumbiaYork UniversityUniversity of Regina
FundersMinistère de l’Éducation, Gouvernement de l’Ontario
KeywordsAgency (philosophy)Digital literacyEllPedagogyLiteracyImmigrationDigital mediaSociologyPopulationTeaching methodComputer sciencePolitical scienceSocial scienceWorld Wide WebVocabulary development

Abstract

fetched live from OpenAlex

In this article, we present findings of a research study centered around a 10-week digital production workshop developed specifically for families in an urban school board, a population rich with culturally diverse immigrant families and English language learners (ELLs). The aim of this research was to support parents/guardians in an urban community in their development of a practical, hands-on understanding of twenty-first century literacies, using a ‘production pedagogy’ framework that emphasizes learner agency. We sought to critically reflect, alongside parents/guardians, on how new media and new literacies are being utilized in schools today, and to provide models, tools and practices for parents/guardians and their children to enact digital competences together, specifically, through the production of a short digital story.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.086
GPT teacher head0.401
Teacher spread0.315 · 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