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Record W7132171539

Kering: Blazing a Trail in Sustainable Luxury

2022· other· en· W7132171539 on OpenAlexaff
Jinyu He, Wenting Xue

Bibliographic record

VenueCEIBS Institutional Repository · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsGallon (US)ClothingSustainabilityRaw materialTextile industryProduction (economics)Greenhouse gasCarbon footprint
DOInot available

Abstract

fetched live from OpenAlex

The fashion industry became the world's third-largest manufacturing sector after the automobile and technology. However, this industry was also notorious as the second-largest water-consuming sector, a top-ten emitter of greenhouse gases, and consumer of raw materials. Dyeing and finishing textile products resulted in 20% of global water pollution and consumption. Fundamentally, it took about 700 gallons of water to produce one cotton shirt and about 2,000 gallons of water for a pair of jeans, equivalent to one person drinking eight cups of water per day for three-and-a-half years and ten years, respectively. Washing garments released 16 times more microfibers than plastic microbeads from cosmetics. In terms of the raw materials used in the supply chain, clothing, footwear, and household textiles ranked the fourth highest category after food, housing, and transport in the EU (see Exhibit 1). Greenhouse gas emissions from textiles production reached 1.2 billion tons of carbon dioxide annually, exceeding international flights and maritime shipping combined. The clothing industry's environmental impact could even worsen as consumer spending in emerging countries and regions increases (see Exhibit 2). The concepts of luxury and sustainability seem to be at odds with each other. People kept skeptical about the source of raw materials of the luxury goods, complained the waste that occurred from production, and criticized the superfluous consumption. However, more and more premium brands and luxury maisons focus on activities that benefit the planet and society. Hermes started using mushroom leather as a sustainable leather alternative while Chanel issued its first public bond linked to sustainability objectives. Prada also partnered with Italian yarn producer Aquafil to launch a new regenerated-nylon made of recycled plastic collected from landfill sites and oceans. Gucci claimed carbon neutrality in their own operations and across their entire supply chain; it aimed to use 100% renewable energy by 2022. Stella McCartney increased the amount of recycled polyester in production, which had a 75% lower carbon footprint and 90% less water usage than virgin polyester. Could luxury and sustainability coexist? If so, how should companies and brands design their strategy accordingly?

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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