Beyond ‘vulnerable groups’: contexts and dynamics of vulnerability
Bibliographic record
Abstract
This paper reviews approaches to vulnerability in public health, introducing a series of 10 papers addressing vulnerability in health in Africa. We understand vulnerability as simultaneously a condition and a process. Social inequalities are manifest in and exacerbate three key dimensions of vulnerability: the initial level of wellbeing, the degree of exposure to risk, and the capacity to manage risk effectively. We stress the dynamic interactions linking material and social deprivation, poverty, powerlessness and ill health: risks or shocks and their health impacts are intimately interconnected and reinforce each other in a cycle which in the absence of effective interventions, increases vulnerability. An inductive process which does not begin with an a priori definition or measurement of 'vulnerability' and which does not assume the existence of fixed 'vulnerable groups' allowed us both to re-affirm core aspects of existing conceptual frameworks, and to engage in new ways with literature specifically addressing vulnerability and resilience at the population level as well as with literature - for example in ecology, and on the concept of frailty in research on aging - with which researchers on health and poverty in Africa may not be familiar. We invite conceptual and empirical work on vulnerability in complex systems frameworks. These perspectives emphasize contexts and nonlinear causality thus supporting analyses of vulnerability and resilience as both markers and emergent properties of dynamic interactions. We accept a working definition of vulnerability, and recognize that some definable groups of people are more likely than others to suffer harm from exposure to health risks. But we suggest that the real work - at both intellectual and policy/political levels - lies in understanding and responding to the dynamics, meanings and power relations underlying actual instances and processes of vulnerability and harm.
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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.058 |
| Scholarly communication | 0.010 | 0.020 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".