Bibliographic record
Abstract
The dual income tax combines a progressive tax on labor income and a lower flat rate tax on income from capital. Denmark, Finland, Norway, and Sweden adopted dual income taxes to address a set of tax challenges that arose in the late 1980s and early 1990s. Although developing countries face much different economic, political, and tax environments from the Nordic countries, the dual income tax may be the right solution to the different set of challenges facing many developing countries. Providing separate tax rates for labor and capital income allows countries greater flexibility in addressing tax competition while retaining progressive tax rates for labor income. A dual income tax regime may also allow developing countries to rationalize the taxation of income from active business operations under the personal and corporate tax systems and the taxation of passive investment income under the personal tax system. Developing countries could also use the move to a dual income tax system as an opportunity to make broader reforms in their personal, corporate, and payroll tax systems. Finally, recent tax reforms in Russia, Ukraine, and several countries in Central and Eastern Europe have led to flat tax regimes that generally apply a single tax rate to all types of income above some zero0bracket amount. We contend that a dual income tax may provide policymakers in developing countries with an attractive alternative that addresses tax competition concerns while maintaining a progressive tax on labor income.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".