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Record W2066443461 · doi:10.1108/03074350610671575

Accelerating foreign direct investment flow to Africa: from policy statements to successful strategies

2006· article· en· W2066443461 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueManagerial Finance · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsAthabasca University
Fundersnot available
KeywordsForeign direct investmentGeneral partnershipInternational economicsInternational tradeEconomicsBusinessInvestment (military)Development economicsPolitical scienceFinanceMacroeconomicsPolitics

Abstract

fetched live from OpenAlex

Purpose – The growing investment gap and the declining foreign aid in recent years have compelled many African countries to turn to foreign direct investment (FDI) as a means to avoid development financing constraints. This article seeks to examine the performance of FDI flow to various regions and countries in Africa and the implication(s) on FDI of the recently launched new partnership for Africa's Development (NEPAD) programs. Design/methodology/approach - Explores strategies for accelerating the flow of FDI to Africa, especially the implications of NEPAD programs. Findings -Africa's FDI inflows are highly uneven both between regions and between countries depending on economic and political environment. In addition, if implemented successfully, NEPAD programs would help spur the flow of FDI to Africa. Originality/value - Besides the socio-economic policy recommendations, suggests marketing strategies to help increase the flow of FDI to Africa.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
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 score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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