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Abstract

‘Vulnerability’ is a concept that is employed widely across the field of bioethics. It is also a concept that has been subject to numerous different interpretations, many of which suffer from significant problems as to their adequacy. Such accounts have been criticised as being too narrow, too general or too vague. Failure to provide a satisfactory conceptual analysis has resulted in contentious definitions of the concept being applied or concerns that it is playing no explanatory role through its use.  For example, more and more categories of individuals and groups have been classified as being vulnerable in an ever-increasing range of situations. In turn, this has led to a situation where almost everyone can be classified as vulnerable in some way, thereby undermining the use of the concept as providing a meaningful category in bioethics. Instead of continuing to try to refine the definition in the (futile) attempt to somehow capture all and only those we wish to fall under the concept, I argue we should recognise that such approaches are unlikely to ever offer us a fully adequate account of vulnerability. Moreover, the attempt to treat vulnerability as if it were a substantive concept might actually be problematic for bioethics by deflecting attention away from issues of identifiable ethical concern. Accordingly, I suggest an eliminativist position should be taken towards the concept but that, in doing so, we can still save our widespread use of the term by treating it as a linguistic device. Using it as a form of linguistic marker would still draw our attention to certain kinds of issue – an ethical ‘alert’ that retains its usefulness – but these would be governed by other, better understood ethical theories and concepts.

Forthcoming events

Infectious Disease Seminar Series: Hepatitis B diagnosis, prevention and treatment: laboratory approaches to the elimination agenda

Monday, 06 February 2023, 1pm to 2pm @ BDI Seminar Room LG 0-1, Old Road Campus, Headington, OX3 7LF

Richard Doll Seminar: Edgar Sydenstricker: Household Equivalence Scales and the Causes of Pellagra

Tuesday, 07 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Ethox seminar- Feminist-Ethical Perspectives on Digital (Health) Technologies

Tuesday, 14 February 2023, 11am to 12.30pm @ Big Data Institute, Lower Ground Seminar Room 1, Oxford Population Heath, University of Oxford

Richard Doll Seminar - E-Freeze trial results

Tuesday, 14 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Infectious Disease Seminar Series: Informing on Neisseria gonorrhoeae treatment and management through pathogen genomics

Monday, 20 February 2023, 1pm to 2pm @ BDI Seminar Room LG 0-1, Old Road Campus, Headington, OX3 7LF

Richard Doll Seminar- Triangulation of evidence in aetiological epidemiology: principles, prospects and limitations.

Tuesday, 21 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Aetiological epidemiology is concerned with the identification of causal influences on disease risk. Randomized controlled trials are, when possible, the cornerstone of knowledge as to whether interventions based on aetiological studies are merited. It is not feasible to subject all of the many candidate causes to large-scale RCTs, however, even in situations where they are in principle possible. Triangulation of evidence is an approach that attempts to formally combine findings from different domains to strengthen causal inference. Triangulation embraces the variety of evidence thesis, that inferential strength depends not only on the quantity of available evidence, but also on its variety: the greater the variety, the stronger the resulting support. An essential condition is that the systematic errors and biases are unrelated across different study types. For example, the effect of raising circulating HDL cholesterol on the risk of coronary heart disease can be estimated from RCTs or through Mendelian randomization using genetic variants related to HDL level. Both the results of RCTs and Mendelian randomization studies could be biased. However, the potential biases in one study design would not influence estimates from the other approach: the biases are unrelated to each other. In observational epidemiology approaches that can be applied include the use of negative control exposures or outcomes; the deliberate use of data from contexts in which confounding structures differ; the use of instrumental variables and related approaches, such as regression discontinuity; quasi-experimental studies; the estimation of the expected magnitude of associations generated by confounding and the incorporation of mechanistic data, amongst others. Pre-registration of protocols for the triangulation of evidence increases confidence in the findings produced.