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Record W2789119096 · doi:10.5539/jms.v8n1p20

Waste Management and Sustainability: Indicators under Ecological Economy Perspective

2018· article· en· W2789119096 on OpenAlexvenueno aff
Natália Molina Cetrulo, Tiago Balieiro Cetrulo, Sylmara Lopes Francelino Gonçalves‐Dias, Rodrigo Martins Moreira

Bibliographic record

VenueJournal of Management and Sustainability · 2018
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSustainabilityPerspective (graphical)Sustainability organizationsTheme (computing)Environmental resource managementEconomicsBusinessEnvironmental economicsEcologyComputer science

Abstract

fetched live from OpenAlex

For indicators to assess a society’s sustainability it is necessary that the understanding of what type of sustainability one wishes to measure is clear. The hypothesis tested in the present study is that solid waste management indicators, used in city sustainability assessments, do not represent the concept of strong sustainability. To test the hypothesis, the article initially identifies the perspectives of solid waste management from the strong sustainability’s point of view, under Ecological Economy perspective. The hypothesis was tested in thirteen sustainability assessment tools, covering approximately 400 cities. Two, out of five perspectives identified, had indicators selected represent them. Only one system presented three perspectives, and eight presented two. To represent the theme’s complexity, all perspectives should be considered, so the hypothesis formulated was accepted.

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)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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