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Gaining and Losing Pieces of the Supply Chain

2003· article· en· W2167317437 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.

Bibliographic record

VenueJournal of Supply Chain Management · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsWestern University
Fundersnot available
KeywordsSupply chainPurchasingBusinessOfficerVariety (cybernetics)MarketingUnit (ring theory)Supply chain managementChain (unit)Operations managementIndustrial organizationEconomicsComputer sciencePsychologyPolitical science

Abstract

fetched live from OpenAlex

SUMMARY This research focused on changes in supply chain responsibilities. The primary research question was: What are the reasons (drivers) for major changes in supply chain responsibilities? Over 200 such changes, comprising 158 additions and 44 deletions, were documented in the research. The findings are based on 10 case studies in large multi‐business unit companies, seven head quartered in the United States and three in Europe, representing a variety of industries. Findings indicated three drivers of change for supply chain responsibilities. The chief purchasing officer and his or her staff members had a great deal of influence, particularly in additions to category 1 (acquisition of specific organizational needs) and category 2 (activities within the total supply chain).

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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