Bibliographic record
Abstract
Health in All Policies (HiAP) approach is generally perceived as an intersectoral approach to national or sub-national public policy development, such that health outcomes are given full consideration by non-health sectors. Globalization, however, has created numerous 'inherently global health issues' with cross-border causes and consequences, requiring new forms of global governance for health. Although such governance often includes both state and non-state (private, civil society) actors in agenda setting and influence, different actors have differing degrees of power and authority and, ultimately, it is states that ratify intergovernmental covenants or normative declarations that directly or indirectly affect health. This requires public health and health promotion practitioners working within countries to give increased attention to the foreign policies of their national governments. These foreign policies include those governing national security, foreign aid, trade and investment as well as the traditional forms of diplomacy. A new term has been coined to describe how health is coming to be positioned in governments' foreign policies: global health diplomacy. To become adept at this nuanced diplomatic practice requires familiarity with the different policy frames by which health might be inserted into the foreign policy deliberations, and thence intergovernmental/global governance negotiations. This article discusses six such frames (security, trade, development, global public goods, human rights, ethical/moral reasoning) that have been analytically useful in assessing the potential for greater and more health-promoting foreign policy coherence: a 'Health in All (Foreign) Policies' approach.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".