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Record W4386897048 · doi:10.32920/24156462.v1

A Triple Bottom Line Analysis of Sustainability Trends in the Luxury Fashion Industry: A Topic Modeling Approach

2023· preprint· en· W4386897048 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

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTriple bottom lineSustainabilityFashion industryCorporate social responsibilityBusinessCorporate sustainabilityNewspaperSocial sustainabilityFast fashionSustainability organizationsMarketingPublic relationsAdvertisingPolitical scienceClothing

Abstract

fetched live from OpenAlex

<p>Sustainability currently is a hot topic in the luxury fashion industry. While customers ponder the feasibility of combining sustainability and luxury fashion, many practitioners have already incorporated sustainability as part of their corporate social responsibility initiatives. This thesis analyzed 32 years of digital newspaper articles on Women’s Wear Daily (WWD) to explore sustainability trends based on the Triple Bottom Line (TBL) framework through topic modeling and content analysis. The results empirically support the increased awareness and importance of sustainability in the luxury fashion sector over time, provide theoretical implications for applying the TBL framework to the longitudinal dataset, and offer insights to business practitioners on expanding their sustainability efforts in the luxury fashion industry. </p>

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.007
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.156
GPT teacher head0.438
Teacher spread0.282 · 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

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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