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Record W3143342760

The Role and Nature of Export Credit Agencies in Foreign Direct Investment: Home and Host States' Coordination and the Problem of Political and Commercial Risks Distinguished

2016· dissertation· en· W3143342760 on OpenAlex
Wael Saghir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSAS-Space (University of London) · 2016
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicLaw, logistics, and international trade
Canadian institutionsnot available
FundersGovernment of CanadaNew Zealand GovernmentGovernment of the United Kingdom
KeywordsForeign direct investmentExpropriationOrder (exchange)Political riskBusinessInvestment (military)PoliticsFinanceMarket economyEconomicsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Since political instability and the fear of expropriation in some developing states pose grave risks to foreign investors, along with the behavior of the financial markets of these states, the need to insure against such risks is something to be considered in order to encourage investments in these regions. ECAs have also been established to assist foreign investors conducting their business in a given market through granting them loans, guarantees and insurance against certain risks encountered by investors. These loans to foreign investors are granted in order to ease their entry into the foreign market so that the recipient market benefits from the expertise and technology that the foreign investor possess.
\nThe study will start with introducing a comprehensive definition for investment in light of the suggested view to what foreign investment stands for. It will highlight the difference between direct and indirect investments as well. Then it will move on to discuss entry of investors to foreign markets and it will discuss the open-door and closed-door approaches in order to identify the various risks associated with such investments. The thesis will emphasize on the need to have a more detailed approach towards investment-risks based on the five-risk distinction rather the classic three-risk approach. This will be of importance especially since the borderline
\nbetween these risks interlink at times.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.535

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 studies0.0000.001
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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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