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Record W2052615177 · doi:10.3808/jei.200600070

Supporting Sustainable Communities with Web-based Information Systems

2006· article· en· W2052615177 on OpenAlexafffund
Yiyu Yao

Bibliographic record

VenueJournal of Environmental Informatics · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Regina
FundersUniversity of Regina
KeywordsAdaptabilityKnowledge managementAdaptation (eye)Situational ethicsSustainable developmentWork (physics)Sustainable communityComputer scienceBusinessEngineeringPolitical science

Abstract

fetched live from OpenAlex

Computer and information technologies have been used to support human activities towards sustainable development. Sustainable community activities are multi-disciplinary and multi-sectoral collaboration for solving environmental, economical and social problems in sustainable ways. However, the current supporting tools are independent and optimized to perform specific functions. This situation limits adaptability with respect to diversity and situational adaptation of sustainable community activities. The Web provides a foundation for supporting human activities and it helps users focus on the work they are trying to accomplish. This paper studies sustainable community activities and their relationships. Based on possible support to various activities, we propose a web-based support system for sustainable communities. It is hoped that the new system will satisfy the needs of sustainable communities.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.304
Teacher spread0.271 · 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 designSimulation or modeling
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

Citations16
Published2006
Admission routes2
Has abstractyes

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