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Record W2811066556 · doi:10.3390/su10072270

Key Issues in Slow Fashion: Current Challenges and Future Perspectives

2018· article· en· W2811066556 on OpenAlexaff
Róbert Štefko, Vladimira Steffek

Bibliographic record

VenueSustainability · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsClothingFast fashionSustainabilityKey (lock)Fashion industryCompetition (biology)Position (finance)Current (fluid)BusinessMarketingComputer scienceProcess managementEngineeringPolitical scienceComputer security

Abstract

fetched live from OpenAlex

The study seeks to explore and synthesize current issues in Slow Fashion and discuss potential future directions of the industry. While there are multiple definitions of the term, Slow Fashion typically describes long-lasting, locally manufactured clothing, primarily made from sustainably sourced fair-trade fabrics. It affords latitude to individual style, fosters education about clothing and emphasizes durability. While several challenges regarding the implementation of Slow Fashion principles in current society remain, the study offers an overview of the current state, and presents a fashion matrix-based framework for outlining the position of the Slow Fashion movement within industry-specific fashion segments and uses the matrix to present current knowledge and review future challenges. The support of networks serves as an indispensable tool for Slow Fashion designers, keeping them abreast of the competition.

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)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0040.013
Scholarly communication0.0150.021
Open science0.0020.006
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0170.003

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 head0.027
GPT teacher head0.285
Teacher spread0.258 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations121
Published2018
Admission routes1
Has abstractyes

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