Beneath the rhetoric of global justice: Reinforcement of global hegemonic governmentality by South Korea’s Global Vaccine Hub Project
Bibliographic record
Abstract
BACKGROUND: During the coronavirus disease 2019 pandemic, the South Korean government initiated the Global Vaccine Hub Project (GVHP) purportedly to address global vaccine inequality. This study analyzes the strategies and underlying epistemology of GVHP through the perspective of global governmentality. Critical Discourse Study (CDS) approaches were used to identify governmental technologies and explain how their embedded knowledge is related to power relations. RESULTS: The findings reveal that GVHP merely pursues national interests by implementing governmental technologies, such as calculative practice, support to private companies, patent protection and circumvention, and pursuing vaccine diplomacy. The South Korean government considered the pandemic an economic and diplomatic opportunity to become an advanced country. The governmental strategies resulted in the depoliticization of vaccines and facilitated the government's opposition to other alternatives, such as an intellectual property waiver at the World Trade Organization level. CONCLUSION: This study argues that the failure of global pandemic governance does not imply the failure of global governmentality; rather, the success of neoliberal global governmentality made global solidarity challenging.
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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 | 0.019 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.055 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".