MétaCan
Menu
Back to cohort
Record W4414453920 · doi:10.17323/1996-7845-2025-02-03

Global Financial Crises and Their Impact on Corporate Finance

2025· article· en· W4414453920 on OpenAlexaboutno aff
Sergei Neklyudov

Bibliographic record

VenueInternational Organisations Research Journal · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceRestructuringCorporate financeFinancial crisisSanctionsBankruptcyQuarter (Canadian coin)Corporate action

Abstract

fetched live from OpenAlex

The article examines how global financial crises and cataclysms that took place in the first quarter of the 21st century affected the corporate finance system. Such aspects of corporate finance as the internal control system, corporate governance principles, risk assessment, management and financial reporting are considered. Based on the analysis of publicly available information, statistical data and regulatory documents, the main changes in the above-mentioned areas of corporate finance that took place after the bankruptcy of Enron in 2001, the crisis in the US mortgage market and the subsequent financial crisis of 2008, the impact of the sanctions since 2014, as well as the consequences of the COVID-19 pandemic in 2019 are identified. Among the key factors that have influenced corporate finance, the following stand out: the growth in the number and diversity of regulatory requirements and restrictions (management and monitoring of regulatory compliance has become a separate and important area in corporate finance); a significant increase in the complexity and multifactorial nature of financial models and various forms of reporting; a reduction in the “planning horizon”, and an increase in the speed of business response and readiness for constant and unexpected changes in strategy, operational management, restructuring and rapid adaptation of existing business processes and systems.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.088
GPT teacher head0.366
Teacher spread0.278 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInternational Organisations Research JournalSame topicGlobal Financial Crisis and PoliciesFrench-language works237,207