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Record W3206235757

Will Reshoring of Textile and Apparel Manufacturing Rise or Decline in the USA

2021· article· en· W3206235757 on OpenAlexaff
Samit Chakraborty, SM Fijul Kabir, Md. Saiful Hoque, Tirtha Sarathi Das

Bibliographic record

VenueJournal of textile and apparel technology and management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsClothingConsumption (sociology)Textile industryBusinessTextileClothing industryPosition (finance)CommerceIndustrial organization
DOInot available

Abstract

fetched live from OpenAlex

The clothing consumption in the USA has been increasing exponentially since last two decades. This increase in consumption has also expanded the fashion retailing business in the USA. For the last few years, there have been different claims and counterclaims on whether reshoring initiative will rise or decline. A group of people thinks that reshoring trend has taken reverse turn and declined gradually. In contrast, other group has stated that the increased offshore production costs and growing demand of ‘Made-in- USA’ products among American retailers and consumers have elevated reshoring movement in the USA. Academic and market research investigations revealed that recently reshoring of textile and apparel manufacturing has significantly impacted on the retailing industry so as the overall economy through creating myriad job opportunities. This comparative position paper presents the promising growth reshoring of textile and apparel manufacturing industries based on the dissection of claims and counterclaims.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.238
Teacher spread0.225 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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