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Record W2743976300 · doi:10.5539/jms.v7n3p101

Brazilian National Solid Waste Policy Applied As a Tool to Enhance an University Campus Waste Management

2017· article· en· W2743976300 on OpenAlexvenueno aff
Rodrigo Martins Moreira, Tiago Balieiro Cetrulo, Alejandra Daniela Mendizábal-Cortés, Natália Molina Cetrulo, Tadeu Fabrício Malheiros

Bibliographic record

VenueJournal of Management and Sustainability · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsStandardizationSolid waste managementContext (archaeology)Municipal solid wasteBusinessWork (physics)National PolicyEnvironmental planningWaste managementEngineeringPolitical scienceEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

The aim of this work is to discuss the Brazilian National Solid Waste Policy potential to enhance Brazilian universities waste management by analyzing the University of São Paulo, Campus of São context in accordance with the national policy requirements. Universities in Brazil lack a legal instrument to strengthen its waste management, which brings this paper innovation by applying the Brazilian waste policy as a standardization instrument to adapt waste management at Brazilian higher education institutions. The research used a descriptive and qualitative approach, data were collected from literature review, university documents and semi structured interviews, a case study approach is used to analyze the campus solid waste management activities, procedures and operations inherent the. The main findings conclude that University of São Paulo waste policy is being deployed, based on Brazilian Solid Waste National Policy requirements, confirming it translation into a potential framework tool to support decision making for adequacy of environmentally sound management of Brazilian. Further studies are required ex-post the policy enactment to assess the impacts of the waste policy at the university impacts.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.347
Teacher spread0.339 · 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
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
Published2017
Admission routes1
Has abstractyes

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