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Information Literacy and the Circular Economy in Industry 4.0

2020· book-chapter· en· W3040541268 on OpenAlexaffabout
Selma Letícia Capinzaiki Ottonicar, Jean Cadieux, Elaine Mosconi, Rafaela Carolina da Silva

Bibliographic record

VenueAdvances in business strategy and competitive advantage book series · 2020
Typebook-chapter
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCircular economyInformation literacyContext (archaeology)SustainabilityLiteracyInformation economyKnowledge economyCritical literacyIndustry 4.0BusinessKnowledge managementPublic relationsPolitical scienceEconomyEngineeringEconomicsEconomic growthComputer scienceGeographyWorld Wide Web

Abstract

fetched live from OpenAlex

Industry 4.0 contributes to the increase in technological production and the use of environmental resources. Because of that, researchers need to discuss circular economy issues in the context of I4.0. To understand the circular economy, people need to know how to access, evaluate, and use the information (information literacy). The purpose of this chapter is to discuss how information literacy has been studied for the development of the circular economy. The methodology implies a review of the literature on circular economy, information literacy, and Industry 4.0. Subsequently, the document connects the information literacy and BNQ21000 standard (Québec) focusing on sustainability. The review showed that there are only a few documents that analyze the circular economy in the context of Industry 4.0. In addition, the information literacy needs to be studied in the circular economy and Industry 4.0 so that managers, students, and researchers can contribute to that revolution in a critical and sustainable way.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.005
Open science0.0000.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.201
Teacher spread0.197 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes2
Has abstractyes

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