Missing Africa: Should U.S. International Tax Rules Accommodate Investment in Developing Countries?
Bibliographic record
Abstract
THE CASE FOR AND AGAINST USE OF AN EXEMPTION SYSTEM TO INCREASE INVESTMENT IN AFRICA Just as the case for invigorating trade and other relations with Africa may not be readily apparent to some, the case for revising those features of the U.S. tax system that disfavor investment in the sub-Saharan world is not intuitive. Although European countries, Mexico, Canada, Japan, and some developing nations, such as China, India, and Venezuela, have commanded partnerships with the United States, African nations have not. A continent of vast natural resources and a considerable labor force, Africa is nonetheless “one of the last regions … to enter the global economy.” The African continent contains a total population of about 778,000,000. Sub-Saharan Africa includes two-thirds of that total, or 642,800,000, among forty-four countries. To date, the situation of much of Africa in the new economy has been that of aid recipient, region of civil and inter-nation strife, location of catastrophic natural disasters, scene of devastating illness, and situs of relentless poverty and shortened life expectancy. Implicit in President Clinton's campaign to eliminate debt of some of the poorest African nations was an acknowledgment of the critical needs of a population for which annual per capita gross national product ranges from $110 to $4,120. Although the debt relief initiative seems well-intentioned, it may have minimal positive impact on the lives of residents of sub-Saharan Africa. Actual provision of relief has been tied to enumerated improvements in infrastructure, including education, health care, transportation, and economic reforms, which fewer than a handful of nations may achieve in the foreseeable future.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".