PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 21, 2026Urban Studies0 citations

Making the case for community-responsive circularity: Lessons from a legacy textile manufacturing region

View Full Paper
NLNichola LoweSKSophie KelmensonMHMolly Hemstreet

Key Points

  • The study aims to explore how innovations in material circularity can promote social inclusion and positive community outcomes.
  • Analyzed the case of Material Return, a textile initiative in Western North Carolina.
  • Examined the transformation of textile waste into high-quality fiber and yarn.
  • Investigated institutional arrangements supporting smaller firms and job stability.
  • Material Return successfully combines material recirculation with social equity enhancements.
  • The initiative stabilizes jobs and elevates worker voices in the textile industry.
  • Findings suggest that community-based approaches can effectively align sustainability with social goals.

Abstract

Circularity means extending the life of resources that would otherwise end up in a landfill. But recirculation is not limited to material resources. Social networks, community assets, and industrial traditions can also be repurposed, raising the question: how can innovations in material circularity be attentive to social inclusion and outcomes? We address this through the case of Material Return, a textile initiative in Western North Carolina that transforms textile waste into high-quality fiber and yarn while supporting smaller firms, stabilizing jobs, and elevating worker voice. By highlighting the enabling institutional arrangements and practices that allow Material Return to combine material and societal circularity, this case offers lessons for other cities and regions seeking to align environmental sustainability with social equity.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Lowe et al. (2026) studied this question.

synapsesocial.com/papers/69be35f96e48c4981c67489fhttps://doi.org/10.1177/00420980261423013
Ask AI
Helpful
Bookmark
Share
View Full Paper