Bibliographic record
Abstract
Striking disparities in access to healthcare and in health outcomes are major characteristics of health across the globe. This inequitable state of global health and how it could be improved has become a highly popularized field of academic study. In a series of articles in this journal the roles of power and politics in global health have been addressed in considerable detail. Three points are added here to this debate. The first is consideration of how the use of definitions and common terms, for example 'poverty eradication,' can mask full exposure of the extent of rectification required, with consequent failure to understand what poverty eradication should mean, how this could be achieved and that a new definition is called for. Secondly, a criticism is offered of how the term 'global health' is used in a restricted manner to describe activities that focus on an anthropocentric and biomedical conception of health across the world. It is proposed that the discourse on 'global health' should be extended beyond conventional boundaries towards an ecocentric conception of global/planetary health in an increasingly interdependent planet characterised by a multitude of interlinked crises. Finally, it is noted that the paucity of workable strategies towards achieving greater equity in sustainable global health is not so much due to lack of understanding of, or insight into, the invisible dimensions of power, but is rather the outcome of seeking solutions from within belief systems and cognitive biases that cannot offer solutions. Hence the need for a new framing perspective for global health that could reshape our thinking and actions.
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 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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.108 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".