Made in America: A Comparative Perspective on Country of Origin Labels for Manufactured Products in the United States and Canada
Bibliographic record
Abstract
In the past twenty years the world has seen one of the largest economic changes in modern history: a drastic increase in commodity exports.'This change signifies the growth of global trade and demand for goods and merchandise.2 Today, economies in developing countries compose more than half of the world's gross domestic product.3 These countries' sudden market and economic growth 4 is partially due to the business practice of outsourcing. 5Outsourcing 6 moves all or some of a business's production operations to other parts 1.See When Giants Slow Down, THE ECONOMIST (July 27, 2013), http://www.economist.con/news/briefing/21582257-most-dramatic-and-disruptive-period-emerging-market-growth-world-has-ever-seen. Id. 3. Id.4. Throughout the past couple decades, the rise in emerging markets has caused global economic growth to span across the globe, encompassing developed and developing countries.G.A. Res.65/168, 17, U.N. Doc A/RES/65/168 (Aug. 1, 2011). 5. See Patrick Dixon, Impact of Outsourcing Jobs -Economies of Wealthy and Poor Nations, GLOBALCHANGE.COM, http://www.globalchange.comloutsourcing.htm (last visited Oct. 15, 2014).6. Outsourcing is "[t]he contracting or subcontracting of noncore activities to free up cash, personnel, time, and facilities for activities in which a company holds a competitive advantage."Outsourcing, BUSINESSDICTIONARY.COM, http://www.businessdictionary.com/definition/outsourcing.html(last visited Nov.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".