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Record W2000961164 · doi:10.1177/027046760002000310

Technology, Sustainability, and Development

2000· article· en· W2000961164 on OpenAlexaff
Arnd Jürgensen

Bibliographic record

VenueBulletin of Science Technology & Society · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndustrial ecologySustainabilitySustainable developmentCircular economyProduction (economics)Scale (ratio)Environmental economicsBusinessEcologyEnvironmental resource managementComputer scienceEconomicsBiologyGeography

Abstract

fetched live from OpenAlex

This article critically examines the notion of development and how it has been transformed by concerns about the environment and sustainability. The concept of industrial ecology is explored to clarify the idea of sustainability. Industrial ecology relies on the notion of a circular industrial metabolism as a benchmark to define the notion of sustainability. The problem with modern industrial systems is the linearity of their metabolism, the extensive use of resources, and the generation of waste. To become sustainable, these systems must reduce their use of resources and generate fewer wastes. The idea of a circular industrial metabolism is applied to two models of development: one based on sustainable development as defined in Agenda 21 and relying on globalized production; the second based on local self-sufficiency and small-scale production methods.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.017
Scholarly communication0.0080.006
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.004
GPT teacher head0.214
Teacher spread0.209 · 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
Published2000
Admission routes1
Has abstractyes

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