The Savings Potential of Sino-Indian Free Trade Agreement within Regional Comprehensive Economic Partnership Initiatives
Bibliographic record
Abstract
The ASEAN community as an international institution has proposed to strengthen economic development by widening cooperation with other countries through regionalism.ASEAN has proposed RCEP with six ASEAN FTA partners within the region.There is no FTA yet between some of the non-ASEAN member countries such as India and China.This condition has influenced the conclusion of RCEP because of different interest among the major power countries.This paper has examined the FTA saving potential analysis between India and China as two of the major power countries in the RCEP negotiations.The FTA saving potential of India and China will be analyzed by using exante analysis.India and China are having the different interests of the preferential agreement on the tariff.India has high tariffs barrier to protect its domestic market.Furthermore, India has demanded the other members to liberalize their services market through RCEP negotiation.India and China have been seen as a rivalry from the political point of view.Both countries have the biggest GDP among RCEP member countries.Therefore, India and China participation in RCEP development are essential to be maintained.The economic interdependence between India and China could lead to cooperation through RCEP.The savings potential analysis shows the tariffs that could be negotiated between India and China.India has proposed to dismantle tariff up to 20 years.This paper has calculated the projection of maximum saving potential that includes three scenarios in the calculation: 20 years of dismantling tariff, export growth and utilization rate.RCEP has been developed to build a comprehensive mutual agreement and economic benefit among the members through cooperation.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".