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Record W2939038952 · doi:10.5539/ijef.v11n5p97

The Impact of Foreign Direct Investment, Human Capital on Labour Productivity in Vietnam

2019· article· en· W2939038952 on OpenAlex
Nguyen Tan Vinh

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Economics and Finance · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainability and Innovation in Business
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentProductivityHuman capitalEconomicsForeign capitalInvestment (military)Labour economicsCapital (architecture)Total factor productivityMacroeconomicsEconomic growth

Abstract

fetched live from OpenAlex

Vietnam is a country which has an attractive level of attracting foreign direct investment (Hereafter FDI) in the region with many preferential policies for investors. FDI attraction aims to help economic growth as well as increase the country's labour productivity. Therefore, the author conducted research to the impact of FDI and human capital on labor productivity of Vietnam. With data analysis techniques using ARDL model with data collected from 1990 to 2017, research result shows that FDI has a positive impact on labor productivity in short term and long term. The factor of university qualification (human capital) only has a positive impact on labor productivity in the long term.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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