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Record W4210372706 · doi:10.1177/08404704211058414

Supply chain capacity to respond to COVID-19 in Newfoundland and Labrador: An integrated leadership strategy

2022· article· en· W4210372706 on OpenAlexafffundabout
Anne Snowdon, Michael Saunders

Bibliographic record

VenueHealthcare Management Forum · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsUniversity of Windsor
FundersCanadian Institutes of Health Research
KeywordsSupply chainBusinessSupply chain managementHealth careValue chainEconomic shortageCoronavirus disease 2019 (COVID-19)PandemicProduct (mathematics)Demand chainMarketingIndustrial organizationService managementEconomic growthEconomicsMedicine

Abstract

fetched live from OpenAlex

This provincial case study, one of seven conducted as part of a national research program on healthcare supply chain management during COVID-19, focuses on Newfoundland and Labrador (NL). Faced with the destabilization of its traditional supply chain, NL leveraged an existing centralized healthcare supply chain structure to organize its supply chain response to the pandemic. To overcome product shortages, health leaders collaborated with their local business community and industries to source and procure personal protective equipment and create domestic manufacturing capacity for critical supplies. The healthcare supply chain response in NL demonstrates the value of a highly integrated and centralized healthcare supply chain management strategy. It also makes clear the value of a diversified healthcare supply chain, one which draws on local manufacturing capacity to create a domestic source of critical supplies and overcome shortages from global suppliers.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.300
Teacher spread0.228 · 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.

Study designNot applicable
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

Citations12
Published2022
Admission routes3
Has abstractyes

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