Tax Policy and Tax System in Korea
Bibliographic record
Abstract
Korea is a fascinating country for economists around the world.Policymakers in Korea have always faced a new set of challenges and adjusted to the rapidly changing internal and external environments.For better or worse the Korea's economic performance, its policies and institutions are of great interest to a wide audience and worthy of serious examination.Careful evaluation of the problems, policy responses, and performance of the past help overcome new challenges ahead and make the best use of potential.This volume is a collection of papers written on various occasions in last quarter of century.Most of them were commissioned by concerned authorities or previously published in professional journals and edited volumes.Papers in the volume were written to show how the nation coped with the arduous task of setting up new policy strategy to meet the challenges at the time when each paper was written.In retrospect questions or issues raised and answers or suggestions made are pretty robust and indicative even for today.Though the volume is limited in the subject areas, it throws a great deal of light on answers to the frequently raised questions.I hope that this edited volume and accompanying volume, entitled Fiscal and Public Policy in Korea, serve as a pivot and stimulant in understanding tax policy, fiscal policy, and public policy in Korea.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".