MétaCan
Menu
Back to cohort
Record W2980588608 · doi:10.1002/pra2.115

The efficacy of digital literacy training initiatives led by local community organizations

2019· article· en· W2980588608 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.

Bibliographic record

VenueProceedings of the Association for Information Science and Technology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDocumentationTraining (meteorology)LiteracyInformation literacyPublic relationsDigital literacyMedical educationLocal communityKnowledge managementPolitical sciencePsychologyComputer sciencePedagogyMedicine

Abstract

fetched live from OpenAlex

ABSTRACT This paper describes an in‐progress research study investigating the efficacy of digital literacy training initiatives led by local community organizations, including public libraries. The goal is to generate a theoretical model of factors affecting the efficacy of digital literacy training opportunities led by local community organizations, and to produce recommendations for practice for local community organizations to follow. The study adopts a constructivist grounded theory approach. Data collection is currently underway and involves interviews with administrators of local digital literacy training initiatives and users who participate in the training. As well, observations of the training and a review of documentation regarding the roll‐out of the training are being conducted. Preliminary results will be communicated at the ASIS&T Annual Meeting in Melbourne.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.008
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 head0.011
GPT teacher head0.278
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