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Record W1991891800 · doi:10.1080/17441692.2012.758762

Are transnational tobacco companies' market access strategies linked to economic development models? A case study of South Korea

2013· article· en· W1991891800 on OpenAlexaff
Sungkyu Lee, Chris Holden, Kelley Lee

Bibliographic record

VenueGlobal Public Health · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsSimon Fraser University
FundersNational Cancer InstituteNational Institute on Drug Abuse
KeywordsTobacco industryLiberalizationMarket accessEconomic growthBusinessEmerging marketsPolitical scienceDevelopment economicsEconomicsGeographyMarket economyFinance

Abstract

fetched live from OpenAlex

Transnational tobacco companies (TTCs) have used varied strategies to access previously closed markets. Using TTCs' efforts to enter the South Korean market from the late 1980s as a case study, this article asks whether there are common patterns in these strategies that relate to the broader economic development models adopted by targeted countries. An analytical review of the existing literature on TTCs' efforts to access emerging markets was conducted to develop hypotheses relating TTCs' strategies to countries' economic development models. A case study of Korea was then undertaken based on analysis of internal tobacco industry documents. Findings were consistent with the hypothesis that TTCs' strategies in Korea were linked to Korea's export-oriented economic development model and its hostile attitude towards foreign investment. A fuller understanding of TTCs' strategies for expansion globally can be derived by locating them within the economic development models of specific countries or regions. Of foremost importance is the need for governments to carefully balance economic and public health policies when considering liberalisation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.124
GPT teacher head0.347
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2013
Admission routes1
Has abstractyes

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