Linkages of Malaysian foreign direct real estate investment and trans- pacific partnerships agreement: a literature review
Bibliographic record
Abstract
Foreign direct investment (FDI) is a type of investment on business by an investor coming from another country which that investor has control on the company. Organization of Economic Cooperation and Development or better known as OECD views control as having 10 percent ownership or more of a business. Multi-national corporations (MNCs) in large make foreign direct investments. Trans-Pacific Partnership Agreement (TPPA) is a free trade agreement that will open up possible frade and investment between 12 countries namely New Zealand, Australia, Canada, Chile, Peru, Japan, Malaysia, Mexico, Brunei, Singapore, United States of America and Vietnam. The treaty was signed by the countries but has not yet entered into force. This paper provides a critical review through literature review on Foreign Direct Real Estate Investment (FDREI) in Malaysia and other parts of the world. This study also intends to highlight the linkages of Malaysian FDREI and TPPA through a previous literature review. The paper is organised by looking at the aspects of FDI, advantages and disadvantages of Foreign Direct Real Estate Investment (FDREI) in terms of socioeconomy, politics, environment, education, security and treaty as well as technology. The last section looks at the linkage between FDREI and TPPA for future research in this growing area of real estate investment.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".