Trade in intangibles and a global value chain-based view of international trade and global imbalance
Bibliographic record
Abstract
This paper aims to develop a framework for the measurement of global trade that integrates trade-in-intangibles and trade-in-goods in the context of globalisation, fragmentation of production activities and increasing trade in intangibles, and applies it for the analysis of global trade imbalance. Through in-depth discussions of the five modes through which trade-in-tangibles are carried out, it develops a framework of international trade measurement from the perspective of global value chains. The overall trade deficit of the U.S. reduced nearly half of its size from USD750 billion to USD396 billion in 2016 with a cautious adjustment without taking into account the intangibles income to most of the U.S. firms accrued through outsourcing activities. It argues that the global trade imbalance and policy responses to solve it should be discussed on the basis of a framework that fully incorporates different types of trade activities in the 21st century. Re-distribution of income from the entities who gained greatly from the trade in intangibles to the rest of the society is crucial to reduce the inequalities. Tax avoidance by depositing these benefits at different locations globally should be curbed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".