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Record W7095574508

THE EXTENT TO WHICH DEVELOPING COUNTRIES ARE INVOLVED IN INTERNATIONAL FINANCIALFLOWS AND THE MAIN EFFECTS ON ECONOMIC DEVELOPMENT

2016· article· en· W7095574508 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentDeveloping countryOrder (exchange)Quarter (Canadian coin)Volatility (finance)LimitingCompetition (biology)Capital flowsFinancial market
DOInot available

Abstract

fetched live from OpenAlex

Foreign direct investments are an important factor for economic growth and development. Throughout time, the source and destination of foreign direct investments have undergone significant changes and thus, starting with the 2000’s there has been an increasingly more global involvement of developing countries in the global flow of foreign direct investments. These countries are currently accountable for more than a quarter of the global outward FDI flows and for almost half of the total global inward FDI flows. In light of the changes that have occurred worldwide after the global financial crisis, the economic policy measures tend to vary from encouraging FDI’s to limiting them. If some countries see FDIs as an important factor for economic growth and global expansion, others only perceive the strong competition from foreign companies, which can lead to a loss of control over domestic capital. At the same time, as the North-South disparity faded, there is evidence that developing countries have become more involved in international financial flows during the past few years. In order to highlight this issue, we have analysed the existing data for a period that has seen a strong financial integration of emerging markets and a decreased volatility of financial flows in advanced industrialised countries (1970-2013). We will particularly approach the relationship between economic growth and international capital flows, with specific reference to foreign direct investment flows (FDI).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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