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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
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