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Record W4322629652 · doi:10.3390/su15054250

Integrating Product Stewardship into the Clothing and Textile Industry: Perspectives of New Zealand Stakeholders

2023· article· en· W4322629652 on OpenAlexaff
Lauren M. Degenstein, Rachel H. McQueen, Naomi Krogman, Lisa S. McNeill

Bibliographic record

VenueSustainability · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsSimon Fraser UniversityUniversity of Alberta
Fundersnot available
KeywordsStewardship (theology)BusinessStakeholderProduct (mathematics)Circular economyEnvironmental stewardshipClothingGovernment (linguistics)IncentiveMarketingExtended producer responsibilitySustainabilityEnvironmental resource managementIndustrial organizationEnvironmental economicsEconomicsManagement

Abstract

fetched live from OpenAlex

The clothing and textile industry has become one of the world’s greatest polluters as tremendous volumes of clothing are produced, used, and disposed of at alarming rates. The industry must transition from its linear take-make-waste model towards a circular economy where textile products are kept in circulation and waste is minimized or eliminated. Product stewardship, an environmental management strategy where producers take responsibility for their products through design to the end-of-life stage, is one option to enable the circular economy. The aim of this research was to explore stakeholder drivers, barriers, and strategies for product stewardship participation in New Zealand. Qualitative data gathered through interview and survey methods of 25 stakeholder perspectives including designers, manufacturers, and retailers were analysed for emerging themes. Key findings suggest that product stewardship operating within the current linear system can only go so far; changes must occur at every stage of the value chain with all stakeholders making efforts towards circularity. Given the complexity of the product stewardship system, greater government regulation and incentive policies are likely needed to mainstream product stewardship and increase its material impact. The results of this study highlight the importance of contextual factors and capacities for tailoring regional product stewardship schemes to local needs.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.588
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.265
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations27
Published2023
Admission routes1
Has abstractyes

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