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Record W4225129471 · doi:10.1080/20430795.2022.2069663

Canadian banks and their responses to COVID-19 – stakeholder-oriented crisis management

2022· article· en· W4225129471 on OpenAlexafffundabout
Eduardo Ordonez‐Ponce, Truzaar Dordi, David Talbot, Olaf Weber

Bibliographic record

VenueJournal of Sustainable Finance & Investment · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of WaterlooÉcole Nationale d'Administration PubliqueAthabasca University
FundersAthabasca University
KeywordsCrisis managementStakeholderPandemicBusinessProxy (statistics)Coronavirus disease 2019 (COVID-19)Financial crisisPublic relationsAccountingPolitical scienceEconomicsManagementMedicine

Abstract

fetched live from OpenAlex

The financial sector is essential to the stability of markets in times of crisis and during the pandemic, banks are called to contribute to society by easing access to credit or keeping rates low. This article explores Canadian banks’ responses to the pandemic assessing their products, services and stakeholders. Using crisis management and stakeholder theories, 3161 news articles about the five biggest Canadian banks and the pandemic were assessed as a proxy for banks’ responses to the pandemic using sentiment analysis, text mining, and statistical methodologies. Results show that banks were negatively impacted by the pandemic and that their stakeholders were approached differently highlighting the community over clients and employees. This study contributes to the need to adapt crisis management strategies and theories to unexpected crises, as others may come, and it sheds some light on stakeholder management measurement processes, which speak to how effective stakeholder management is.

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)0.001
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 score0.700
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.045
GPT teacher head0.253
Teacher spread0.207 · 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

Citations8
Published2022
Admission routes3
Has abstractyes

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