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Record W1519607437 · doi:10.15353/joci.v7i1-2.2565

Garden of Literacies: ICDT Contributing to the Construction of New Realities for Digitally-Excluded Senior Citizens

2011· article· en· W1519607437 on OpenAlexvenueno aff
Ivan Ferrer Maia, José Armando Valente

Bibliographic record

VenueThe Journal of Community Informatics · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisUniversidade Estadual de CampinasConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsInformation and Communications TechnologySociologyDigital literacyConvergence (economics)Digital cultureLiteracyPedagogyComputer scienceMedia studiesWorld Wide WebEconomic growth

Abstract

fetched live from OpenAlex

This paper shows how digitally-excluded senior citizens use information and communication technologies (ICT) for the construction of new literacies in the digital convergence culture. The concept of literacies is related to how ICT can be used to expand ways people express themselves through different communication channels. This study lasted three years and involved 16 adults aged between 60 to 78 years. The results showed that they were able to insert themselves into the digital culture with a more critical and creative attitude. Also, during this study it was possible to identify four types of literacies: automatic, functional, conscious and contextual.

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)0.004
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0060.015
Scholarly communication0.0110.006
Open science0.0010.016
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.056
GPT teacher head0.311
Teacher spread0.255 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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