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Record W2131465720 · doi:10.2202/1469-3569.1067

From Protectionism to Regionalism: Multinational Firms and Trade-Related Investment Measures

2004· article· en· W2131465720 on OpenAlexaboutno aff
Kerry A. Chase

Bibliographic record

VenueBusiness and Politics · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
Fundersnot available
KeywordsProtectionismMultinational corporationRegionalism (politics)International tradeNegotiationEconomicsForeign direct investmentArgument (complex analysis)Transatlantic Trade and Investment PartnershipInternational economicsPoliticsFree tradeBusinessPolitical scienceDemocracy

Abstract

fetched live from OpenAlex

Trade-related investment measures (TRIMs) have been a key issue in regional and multilateral trade negotiations, but they have received little attention in theoretical work to date. This article analyzes the political economy of TRIMs to illuminate why regional arrangements have been a popular framework for eliminating them. The main argument is that multinational firms often demand safeguards when TRIMs are being liberalized, particularly if they have large sunk costs due to asset specificity. In general, regional arrangements are better equipped than multilateral rules to incorporate the safeguards these firms demand: regionalism requires governments to make binding commitments, and it creates opportunities to discriminate against outsiders. A case study of lobbying by U.S. companies with FDI in Canada from the early twentieth century to the negotiation of the Canada-United States Free Trade Agreement illustrates these points. The article concludes that regional arrangements are likely to remain more active, and more successful, than multilateral discussions in managing the commitment problems inherent in liberalizing TRIMs.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.021
GPT teacher head0.227
Teacher spread0.205 · 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

Citations15
Published2004
Admission routes1
Has abstractyes

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