Digital is making us rethink global trade
Bibliographic record
Abstract
Globalization and trade from cross-border sales to global value chains A woman in Dusseldorf suffering from pain in her hip is x-rayed in a local hospital. Her x-ray is read and interpreted online by a specialist in Bangalore, who recommends her for hip replacement surgery. Prior to her surgery, her replacement hip joint is custom ‘printed’ in Dusseldorf on a 3-D printer manufactured in Toronto and operated remotely by a technician in Los Angeles. Her surgeon in Dusseldorf who installs the replacement hip, born in Damascus, received his medical training at a university in Shanghai and now works in Germany on a refugee visa. This tale of numerous intermediate and component goods, services, labour, data, and information crossing borders in different ways to deliver a hightechnology medical service needed by one individual is not a narrative of traditional international trade, any more than the complex web of regulations and international agreements governing each element of the service delivered is a product of traditional diplomacy. Trade and the diplomacy that facilitates it are already different today in many areas. They will continue to change in the future. As technologies have emerged and evolved over the past two and a half centuries, the way that products are designed, produced, and marketed has changed, the way that goods are bought and sold has changed. The part that international trade plays in that process has changed as well. Let us begin by examining how new technologies have changed how, and for whom, goods and services are produced. The first round of globalization, which began in the mid-nineteenth century, saw the transformation of the first industrial revolution's technologies of mass production and mechanization into a boom in international trade according to the model expected by the classical political economy theories of Adam Smith and David Ricardo. Producers increasingly produced and exported surpluses of goods (and later services) that used factors of production – labour, land, capital, knowhow – that existed in relative abundance where they were located. Hence their costs to produce these goods and services were relatively low.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; both teacher heads agree on what is shown here.
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".