THE EXTENT TO WHICH DEVELOPING COUNTRIES ARE INVOLVED IN INTERNATIONAL FINANCIALFLOWS AND THE MAIN EFFECTS ON ECONOMIC DEVELOPMENT
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".