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Record W3101193650 · doi:10.18616/rdsd.v6i3.6317

Desenvolvimento pluridimensional e a Agenda 2030: limites e possibilidades à efetivação do consumo sustentável na era “da leveza”

2020· article· pt· W3101193650 on OpenAlexaff
Tuana Paula Lavall, Giovanni Olsson

Bibliographic record

VenueDesenvolvimento Socioeconômico em Debate · 2020
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

O artigo analisa quais os limites e possibilidades à efetivação do consumo sustentável, pontuado como um dos objetivos da Agenda 2030 das Organização das Nações Unidas (ONU), na era “da leveza”, conceito elaborado pelo filósofo Gilles Lipovetsky para descrever a sociedade de consumo contemporânea. De forma específica, explora os aspectos centrais da construção da Agenda 2030 pela ONU; apresenta qual a inserção do consumo sustentável no mencionado documento; e caracteriza os paradoxos do consumo na denominada “sociedade da leveza”. Com o emprego do método dedutivo e utilizando as técnicas de pesquisa bibliográfica e documental, o estudo, que é de cunho teórico e de caráter qualitativo, ensaia uma aproximação entre o paradigma de desenvolvimento endossado pelos países-membro da ONU e as teorizações sobre a cultura do consumo, destacadamente aquelas procedidas por Gilles Lipovetsky. A conclusão é no sentido de que, embora a promoção do consumo sustentável encontre limites na própria tessitura social contemporânea, marcada pelo consumismo, apego ao novo e desperdício, emergem tendências como o consumo ecológico, o comércio justo e o consumo compartilhado, que se apresentam como possibilidades para a efetivação do consumo sustentável.

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)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.022
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0060.008
Scholarly communication0.0180.012
Open science0.0010.008
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.036
GPT teacher head0.271
Teacher spread0.234 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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