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Record W2121063684 · doi:10.1179/102452909x390592

The Financial Thesis: Reconceptualizing Globalisation's Effect on Firms and Institutions

2009· article· en· W2121063684 on OpenAlexfundno aff
Ashby Monk

Bibliographic record

VenueCompetition & Change · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersLupina Foundation
KeywordsGlobalizationConvergence (economics)CapitalismPensionIncentiveSkepticismPath dependenceEconomicsFinancial marketMarket economyBusinessPolitical scienceFinanceEconomic growthNeoclassical economics

Abstract

fetched live from OpenAlex

The relationship between globalisation and institutional change is an issue frequently debated in economic geography and the social sciences. Some see firms, whatever their national culture or heritage, as facing common market forces that undermine self-determination and predict convergence towards a global best practice. Others are sceptical, arguing that different country-specific ‘varieties of capitalism’ have market-distorting effects, resulting in path dependence that limits the strength of global incentives to converge at the firm level. Others still are unconvinced by both these arguments. As such, this paper seeks to better understand globalisation's impact on institutions and firms by documenting the effect of global finance and its affiliated agents on institutions and firms. Specifically, I examine the experiences of firms in both Japan and the US that sponsor pension funds to see if they have had similar experiences and behaviours in both jurisdictions. I find that American and Japanese pension sponsors, despite clear manifestations of societal differences, have in fact had very similar experiences. So, some of the predictions held by path dependence and the varieties of capitalism are not confirmed in this case. However, because convergence towards a ‘best practice’ corporate pension offering is also rejected, the paper concludes that new research that focuses on the impact of financial markets on institutions and firms offers important insights for explaining the outcomes in both places.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.020
Scholarly communication0.0060.013
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.058
GPT teacher head0.249
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2009
Admission routes1
Has abstractyes

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