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Record W3083244312 · doi:10.1016/j.emj.2020.09.002

COVID-19 and business failures: The paradoxes of experience, scale, and scope for theory and practice

2020· article· en· W3083244312 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

VenueEuropean Management Journal · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsWestern University
Fundersnot available
KeywordsPandemicLegitimacyCoronavirus disease 2019 (COVID-19)Scope (computer science)Political economyPoliticsExperiential learningScale (ratio)Positive economicsPolitical scienceBusinessDevelopment economicsPublic relationsEconomicsGeographyComputer scienceDiseaseLaw

Abstract

fetched live from OpenAlex

In light of growing scholarly works on business failure, across the social science domains, it is surprising that past studies have largely overlooked how extreme environmental shocks and 'black swan' events such as those caused by the coronavirus (COVID-19) pandemic and other global crises, can precipitate business failures. Drawing insights from the current literature on business failure and the unfolding event of COVID-19, we highlight the paradoxes posed by novel exogenous shocks (that is, shocks that transcend past experiences) and the implications for SMEs. The pandemic has accelerated the reconfiguration of the relationship between states and markets, increasing the divide between those with political connections and those without, and it may pose new legitimacy challenges for some players even as others seem less concerned by such matters, whilst experiential knowledge resources may be both an advantage and a burden.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.817
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.027
GPT teacher head0.277
Teacher spread0.250 · 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