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Record W6986263148

Patterns of Financialisation: A Multimethod Study of Banking Regulation in Canada

2021· dissertation· en· W6986263148 on OpenAlexaboutno aff

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2021
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDeregulationWageForeign ownershipNational bankFinancial sectorRegression analysisBank credit
DOInot available

Abstract

fetched live from OpenAlex

In this thesis I ask if financialisation – the increasing influence of the financial sector – may cause a dual effect of increased economic growth and decrease wage share of total income. I operationalise financialisation as financial deregulation and test its effects utilising a nested analysis. The results from a regression on OECD-member states from 1991 to 2005 indicate that credit controls as a specific category of financial deregulation decreases economic growth and that deregulation of banking supervisory agencies increases the wage share of total national income. Canada’s Bill C-67 of 1999, deregulating foreign bank entry, is selected as the case to be studied in-depth based on the regression results. I then conduct process tracing on theorised mechanisms of foreign bank entry in Canada. I find that foreign bank entry in Canada brought economic growth through foreign direct investment. I also find that the wage share of total national income was reduced from credit-led growth and finance-led growth, both of which were results of foreign bank entry.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.012
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.069
GPT teacher head0.265
Teacher spread0.196 · 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 designQualitative
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueDuo Research Archive (University of Oslo)→Same topicDiverse Scientific and Economic Studies→French-language works237,207→