Reconceptualising health security in post-COVID-19 world
Bibliographic record
Abstract
While drawing upon the existing literature and policy documents on health security and its practice at the national and global levels, this article shows that the idea of health security has mostly remained rhetoric or at the most conceptualised and operationalised within the narrow Westphalian tradition of protecting nation states from external threats. By undertaking a critical examination of the national security strategies of some powerful G-20 countries, we show that non-traditional threats such as infectious diseases and pandemics are either absent from the list of potential threats or are accorded a weak priority and addressed within the state and military-centric notion of security. This approach has shortcomings that are laid bare by the ongoing pandemic. In this article, we show how national and global health security agendas can be advanced much more productively by mobilising a wider securitisation discourse that is driven by the human security paradigm as advanced by the United Nations in 1994, that considers people rather than states as the primary referent of security and that emphasises collective action rather than competition to address the transnational nature of security threats. We discuss the relevance of this paradigm in broadening the concept of health security in view of the contemporary and future threats to public health.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".