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Record W2970016687 · doi:10.17323/1996-7845-2019-01-07

The Dynamics of the Canadian Insurance Market Under NAFTA

2019· article· en· W2970016687 on OpenAlexaboutno aff
Валентина Демчук

Bibliographic record

VenueInternational Organisations Research Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsInternational tradeInternational economicsDynamics (music)BusinessPolitical sciencePhysics

Abstract

fetched live from OpenAlex

within the framework of the North American Free Trade Agreement (NAFTA). The development of the world economy leads to the growing influence of economic integration, including integration in the insurance sector. Globalization makes it necessary for countries to work together to improve the stability of national financial systems. Along with the positive effects of integration, such as higher trade volumes, there are also negative repercussions, such as local producers being driven out of the market. The effects and risks associated with the influence of integration groups, identified in the course of research and discussions in economics, can be verified (or falsified) empirically on the basis of data on the development of national insurance markets within the framework of integration groups. Based on statistical data, econometric models were built to determine the effect of NAFTA on the Canadian insurance market by assessing the extent to which the changes in quantitative indicators of the development of the insurance market in Canada, namely the premium volume, insurance density and penetration, are due to the agreement. Based on existing insurance market research, a number of economic and social factors were selected as macroeconomic parameters affecting the premium volume. The author concludes that being a member of NAFTA does not affect the selected quantitative insurance development indicators in Canada. The author assumes this to be one of the reasons

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.820
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.371
Teacher spread0.335 · 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 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

Citations4
Published2019
Admission routes1
Has abstractyes

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