KT&G: From Korean monopoly to ‘a global name in the tobacco industry’
Bibliographic record
Abstract
Until the late 1980s, the former South Korean tobacco monopoly KT&G was focused on the protected domestic market. The opening of the market to foreign competition, under pressure from the U.S. Trade Representative, led to a steady erosion of market share over the next 10 years. Drawing on company documents and industry sources, this paper examines the adaptation of KT&G to the globalization of the South Korean tobacco industry since the 1990s. It is argued that KT&G has shifted from a domestic monopoly to an outward-looking, globally oriented business in response to the influx of transnational tobacco companies. Like other high-income countries, South Korea has also seen a decline in smoking prevalence as stronger tobacco control measures have been adopted. Faced with a shrinking domestic market, KT&G initially focused on exporting Korean-manufactured cigarettes. Since the mid-2000s, a broader global business strategy has been adopted including the building of overseas manufacturing facilities, establishing strategic partnerships and acquiring foreign companies. Trends in KT&G sales suggest an aspiring transnational tobacco company poised to become a major player in the global tobacco market. This article is part of the special issue 'The emergence of Asian tobacco companies: Implications for global health governance'.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".