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Record W2945940214 · doi:10.2495/sdp-v14-n2-172-182

A social sustainability assessment model for manufacturing company based on S-LCA

2019· article· en· W2945940214 on OpenAlexvenueno aff
Junli Shi, Yajun Wang, Qinyi Ma, Shuagjiao Fan, Haihua Jin, Huanyu Liu, Huan Liu

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2019
Typearticle
Languageen
FieldEngineering
TopicSustainable Industrial Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBusinessSocial sustainabilityLife-cycle assessmentManufacturing engineeringEnvironmental economicsEngineeringEconomicsProduction (economics)

Abstract

fetched live from OpenAlex

generally, sustainability analysis should include the aspects of the environmental, social, and economic assessment.The development of social sustainability assessment for manufacturing company however has been paid little attention currently, and previous studies are not appropriate due to the complex information and the unbefitting indicators.This study presents a new social sustainability assessment model based on social life cycle assessment (S-lcA) methodology to assess the social sustainable performance for manufacturing companies, in this method, four groups of stakeholders and social impact categories are involves and product social risk score (PSrS) is employed to quantitatively expressed the sustainability indicator of the company.Through detailed social inventory investigation, fuqiang Power company as the research case is put to assess the social sustainability and verify the validity of this model.

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)0.001
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.289
Teacher spread0.268 · 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
GenreMethods

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

Citations8
Published2019
Admission routes1
Has abstractyes

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