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Record W2094595986 · doi:10.5430/wje.v5n2p78

The Importance of Sustainable Digital Inclusion Projects in Brazilian Education

2015· article· en· W2094595986 on OpenAlexvenueno aff
Francisco Roberto Ferreira dos Santos, Ildefonso Rodrigues Teixeira

Post-publication record

NatureRetraction
ReasonNotice - Limited or No Information;Removed;
Date3/6/2016 0:00
Flagged by OpenAlex?No. Retraction Watch records this, and OpenAlex does not flag it.

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueWorld Journal of Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)PsychologyPedagogyEnvironmental planningGeographySocial psychology

Abstract

fetched live from OpenAlex

The implementation of digital devices represents one of the main educational trends in recent years, alongside theimprovement in wireless connections potential. Many political initiatives have addressed development andinnovation issues through projects of digital inclusion, often taking for granted that access to Information andCommunication Technologies is the main factor to produce differences in social, cultural and economic outcomes.This paper goes beyond this deterministic vision, in favor of a broader concept of digital inclusion. The frameworkproposed is a model based on cultural needs analysis and subsequent promotion of didactics innovation, alongsidethe enhancement of competences development, both from teachers and students. The main goal is to present asustainable approach to digital inclusion, having as a focus methodological training for teachers.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.026
GPT teacher head0.354
Teacher spread0.328 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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