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Record W3190644561 · doi:10.1177/00081256211066635

Global Value Chain Resilience: Understanding the Impact of Managerial Governance Adaptations

2022· article· en· W3190644561 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCalifornia Management Review · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsRestructuringCorporate governanceGlobal value chainBusinessShock (circulatory)Value (mathematics)Resilience (materials science)Psychological resilienceTerm (time)PandemicControl (management)Coronavirus disease 2019 (COVID-19)Industrial organizationEconomicsInternational tradeFinanceManagementComparative advantage

Abstract

fetched live from OpenAlex

While COVID-19 has caused significant short-term disruptions in global value chains (GVCs), in the longer run, the pandemic will not be the primary catalyst in GVC evolution. As GVCs recover from the initial shock, managers will make GVC restructuring decisions guided by long-term strategic considerations. This article describes barriers that lead firm managers may encounter when rethinking location/control decisions for value chain activities and suggests that, in addition to structural changes, managerial governance adaptations are instrumental in enhancing GVCs’ long-term resilience. Lessons learned from responding to the pandemic can help managers enhance GVC efficiency in the increasingly uncertain global environment.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.032
GPT teacher head0.296
Teacher spread0.264 · 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