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Record W6920974686 · doi:10.6084/m9.figshare.12248282

Foreign Direct Investment

2020· article· en· W6920974686 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2020
Typearticle
Languageen
FieldComputer Science
TopicCOVID-19 Digital Contact Tracing
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentExtant taxonChinaInvestment (military)Quarter (Canadian coin)Developing countryBridging (networking)

Abstract

fetched live from OpenAlex

Foreign direct investment (FDI) implies a lasting interest by an enterprise resident in one country in another enterprise in another country. The estimated global flow of FDI for 2012 is 1.4 US$ trillion. In the first two quarters of 2012, transition in developing countries attracted over 50% of global FDI for the first time. China was the largest recipient country in the same period, followed by the United States. Direct investment is viewed as a method of securing determining influence on the overseas operation. Investors tend to provide other resources such as knowledge, management techniques, technology, and marketing strategy. FDI is a strategic option for firms that undertake it and for the states that seek to attract and regulate it. Managerial players are free to make and implement strategic choices, albeit within the limits of the structural circumstances they find themselves in. The practice of FDI in the last quarter of the twentieth century has been growing rapidly. Three groundbreaking intellectual perspectives spurred by Coase, Hymer, and Penrose provided the initial tremors causing the paradigm to begin to shift. Until a theory of the transnational enterprise and FDI emerges that is capable of bridging the epistemological gap that separates its territory from that of international strategic management (ISM), Dunning's OLI framework will be taken to be the extant theory of transnational enterprise.

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)0.002
metaresearch head score (Gemma)0.010
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.293
Threshold uncertainty score0.979

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2930.238

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 head0.086
GPT teacher head0.262
Teacher spread0.176 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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