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Record W7001353360

Investitiile straine directe in regiunea Central Est Europeana

2023· other· en· W7001353360 on OpenAlexaboutno aff

Bibliographic record

VenueMunich Personal RePEc Archive (Munich University) · 2023
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentDestinationsStock (firearms)Capital (architecture)Quarter (Canadian coin)Investment (military)
DOInot available

Abstract

fetched live from OpenAlex

This paper aims to examine the specific characteristics of Foreign Direct Investment (FDI) within a well-designed, multi-country region from the perspective of the UNCTAD Organization. It builds upon previous systematic analyses that primarily focused on global levels of international capital flows, where FDI and Direct Investments Abroad (DIA) represent opposite directions of these flows. The reference period for data analysis spans from 1990 to 2015, encompassing a quarter of a century. The results presented in this paper will include the cumulative levels of FDI and DIA stocks within the entire region and individual countries, as well as the stock balances (FDI minus DIA). Furthermore, the paper will explore the regional dynamics, sources, and destinations of capital flows, while also drawing comparisons between the Central and Eastern European (CEE) region and other similar regions worldwide, as identified by UNCTAD using the same international capital framework.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.099
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.017
GPT teacher head0.190
Teacher spread0.173 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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