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Record W3022639051 · doi:10.1111/ijcs.12590

Impact of physical condition on disposal and end‐of‐life extension of clothing

2020· article· en· W3022639051 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Consumer Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsClothingDispose patternBusinessQuality (philosophy)Investment (military)Extension (predicate logic)Operations managementWaste managementEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract Clothing waste is an increasing global problem as “disposable” fashion items are consumed and discarded at rapid rates. Low‐quality fashion garments are easily damaged and thrown out due to the low initial investment and replacement cost of other items. Previous research has found physical damage to be a common reason for clothing disposal; however, the degree to which damage plays a role in disposal decisions has not been studied. Therefore, using a survey‐based, pre‐experimental design, this research examined the extent to which varying levels of garment physical damage influences consumer disposal decisions and garment life extension practices in Edmonton, Canada. Results indicated that damage severity plays a significant role in how respondents choose to dispose, or otherwise deal with, their unwanted clothing. Garment quality and type were also shown to predict disposal method and end‐of‐life extension strategies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.186

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.076
GPT teacher head0.350
Teacher spread0.274 · 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