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Record W4386261060 · doi:10.31864/2447-2921.2023.4924

EFEITO BATOM, SUSTENTABILIDADE E OS IMPACTOS DA PANDEMIA COVID 19 NO CONSUMO NO BRASIL

2023· article· pt· W4386261060 on OpenAlexaff
Francisca Noeme Moreira de Araújo, Marcelo Victor Alves Bila Queiroz, Walid Abbas El-Aouar, César Ricardo Maia de Vasconcelos

Bibliographic record

VenueRevista Conhecimento Contábil · 2023
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)MedicinePhilosophyDisease

Abstract

fetched live from OpenAlex

A pandemia provocada pelo Covid-19 já é considerada uma das maiores da história e afetou diretamente a vida das pessoas, inclusive o consumo, exigindo das organizações rápidas adaptações. A partir desse contexto, este estudo tem como objetivo geral identificar se as pessoas modificaram seus hábitos de consumo no que se refere a produtos de higiene e cuidados pessoal, cosméticos e perfumaria desde o início da pandemia. O processo de coleta de dados aconteceu de maneira online e obteve a participação de 137 pessoas. A pesquisa é de caráter descritiva e quantitativa. Os resultados apontam que as pessoas modificaram o estilo de consumo dos produtos estudados e que o batom deixou de ser o item mais consumido, dando lugar a outros produtos cosméticos e de cuidados com a pele, contrariando os resultados do efeito batom. Além disso, identificou que as questões relacionadas a qualidade, preço e crueltly free, são critérios a serem analisados na escolha desses produtos, embora continuem consumindo produtos de marcas que não são crueltly free.

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)0.006
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 score0.105
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.299
Teacher spread0.242 · 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
Published2023
Admission routes1
Has abstractyes

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