Transnational Corporations and Business Networks in ASEAN: Building Partnership in the Asia– Pacific Region
Bibliographic record
Abstract
There are many factors that promote the close, mutual cooperation within the group of ASEAN countries. These states are linked by the economic, social and political ties. One of the elements that can contribute to the deepening of the integration between the ASEAN countries are the transnational corporations and the business networks they create. Transnational corporations (TNCs) are an economic power in today’s global economy. TNCs are important players and their role is manifested in capital flows, technology transfer and merchandise trade. The importance of corporations as global players is growing due to their economic potential, and also because they make foreign direct investment and create business networks, thereby, contribute to the flow of the state-of-the-art technologies from the developed to the developing countries. They play a significant role in shaping the global economy along with the individual national economies, both those developed ones, from which TNCs mainly originate, and the developing economies, to which they relocate their subsidiaries or chosen elements of the value chain. The aim of this paper is to examine the activities of the transnational corporations in the ASEAN countries and the impact these corporations have on building partnerships between the countries. The analysis will also cover corporations originating from the ASEAN countries, which through creation of business networks, actively affect ASEAN relations with the Asia-Pacific region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| 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".