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Colour, Clothing, and the Concept of ‘Green’: Colour Trend Analysis and Professionals’ Perspectives

2012· article· en· W2068587846 on OpenAlexaff
A.W.C. Chu, Osmud Rahman

Bibliographic record

VenueJournal of Global Fashion Marketing · 2012
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsClothingOrder (exchange)BusinessMarketingAdvertisingPsychologyPolitical science

Abstract

fetched live from OpenAlex

Increasingly, many fashion companies and organizations have introduced slogans such as ‘green is the new black’ and ‘get hip, get green’ to raise ‘green’ awareness as well as to build corporate image. This study was designed to explore industry opinion on what colour(s) is/are more likely associated with the notion of ‘green.’ In order to gain a deeper understanding of the relationship between colour and environmental issues, a self-administered questionnaire survey was used to collect data from various professionals. According to the present study, it is evident that certain colours are viewed to be more eco-friendly than others. The findings of this study provide insight and implications for fashion practitioners, educators and consumers on the concept of eco-friendly in general and colour attribute in particular.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.004
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.332
Teacher spread0.316 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations21
Published2012
Admission routes1
Has abstractyes

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