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Record W4391884683 · doi:10.55905/cuadv16n2-045

Social media and digital accessibility: the impact of the COVID-19 pandemic in the city of Belém (PA)

2024· article· en· W4391884683 on OpenAlexaff
João Paulo Vasconcelos Mendonça, Ronny Luís Sousa Oliveira, Rossicléa Ferreira Do Nascimento, Suzana Saraiva Noronha Monteiro, Mauro Margalho Coutinho, Miralda Souza Martins Dos Prazeres

Bibliographic record

VenueCuadernos de Educación y Desarrollo · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCommunication and COVID-19 Impact
Canadian institutionsImpact
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicSocial media2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SociologyMedia studiesPolitical scienceVirologyComputer scienceMedicineWorld Wide Web

Abstract

fetched live from OpenAlex

The study aims to understand the process of using technological tools, and the possible barriers faced, within the context of the Pará pandemic scenario. The pandemic has transformed the world, isolating people at home by converting homes into offices, classrooms, offices and others. Digital access grew exponentially, it was the mechanism that provided the continuity of the world's dynamics, especially social media, considering the speed of resolution of personal, professional, health and other issues, using tools like WhatsApp, Facebook, mobile applications, among others, within existing technologies (smartphone, tablet, notebook, desktop PC). The survey method for data collection was adopted. Word Excel was used as a statistical analysis process. The results point to ways of improving Internet connection services and new forms of digital tools that can make life easier for their users.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.111
GPT teacher head0.428
Teacher spread0.317 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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