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Record W4390642484 · doi:10.1145/3625008.3625028

Metaverse and cultural preservation: an alternative through NFTs of social sustainability in Brazil

2023· article· en· W4390642484 on OpenAlexaff
Manuella Silva, Adolfo Neto, Carlos Cabada, Karina Bland, Jonas Davanço, João Marcelo Teixeira

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsO/E Land (Canada)
Fundersnot available
KeywordsSustainabilityIndigenousPromotion (chess)Environmental ethicsInclusion (mineral)SociologyEngineering ethicsPublic relationsPolitical scienceSocial scienceEcologyEngineering

Abstract

fetched live from OpenAlex

Exploring the potential of NFTs and metaverses can make them tools for cultural preservation and social sustainability in Brazil. This article provides an overview of the recent evolution of the metaverse and the adoption of these technologies by Brazilian communities. The main focus of this study is on the involvement and inclusion of Indigenous peoples in this technological sphere, emphasizing the importance of ensuring respect and preservation of forest peoples when including them in NFT projects. Several existing solutions that can facilitate social initiatives are exemplified, and one such solution is the 3.land marketplace/metaverse, which holds great potential for social actions due to its community-driven dynamics and 3D education promotion. The article concludes by suggesting possible directions to enhance technological development for Brazil’s Indigenous communities, promoting the appreciation and protection of cultural expressions from the forests through blockchain and cryptocurrency technologies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.639
Threshold uncertainty score0.184

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.057
GPT teacher head0.379
Teacher spread0.322 · 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 designTheoretical or conceptual
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

Citations7
Published2023
Admission routes1
Has abstractyes

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