Jonathan Fuller
Biographic Data
| ID | 3874132 |
|---|---|
| NAME | Jonathan Fuller |
| GIVEN NAMES | Jonathan |
| FAMILY NAME | Fuller |
| SIGNATURE | FULLER J |
| AFFILIATIONS | University of Pittsburgh |
| ORCID | 0000-0002-7598-9808 |
| VERIFIED | Yes |
| TOTAL WORKS | 17 |
| TOTAL CITATIONS | 38 |
| WORKS AS AUTHOR | 17 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Magic bullet or marginal bet—does precision medicine offer the best hope for sick individuals and sick populations
By targeting treatment according to molecular biomarkers, precision medicine promises a revolution in healthcare. We examine this promise by distinguishing three precision medicine strategies: biomarker-stratified-high-risk-targeting, biomarker-based-individual-targeting, and biomarker-based-disease-targeting. Each strategy seeks to boost one of the determinants of the population impact of a medical intervention. We conclude that these strategies…
Demarcating scientific medicine
Scientific medicine and homeopathy are interesting case studies for the ongoing project of demarcating science from pseudoscience. Much of the demarcation literature formulates abstract criteria for demarcating science from pseudoscience generally. In service of a more localist approach to the demarcation problem, I reconstruct a specific demarcating difference, the like comparison criterion, invoked by nineteenth century adherents to an early mo…
Preventive and curative medical interventions
Epidemics from the Population Perspective
Many epidemics consist in individuals spreading infection to others. From the population perspective, they also have population characteristics important in modeling, explaining, and intervening in epidemics. I analyze epidemiology’s contemporary population perspective through the example of epidemics by examining two central principles attributed to Geoffrey Rose: a distinction between the causes of cases and the causes of incidence, and between…
What are the Covid-19 models modeling (philosophically speaking)
Conceptual lessons for containing an epidemic of questionable Covid-19 counterfactual comparisons
The COVID-19 pandemic has provided limitless opportunities to compare pandemic policies across countries and over time. When the aim is to assess the comparative success of these policies, the comparison requires thinking counterfactually about ‘what would have been’ in some unrealised hypothetical (counterfactual) scenario. Whether generating modelling projections,1 making data-driven comparisons across countries2 or attributing excess harms,3 c…
The myth and fallacy of simple extrapolation in medicine
Choosing Words Wisely
PURPOSE: To characterize how residents employ rhetorical appeals (i.e., the strategic use of communication to achieve specifiable goals) when discussing unnecessary diagnostic tests with patients. METHOD: In 2015, senior hematology residents from 10 Canadian universities participating in a national formative objective structured clinical examination (OSCE) completed a resource stewardship communication station. In this communication scenario, a s…
Book Forum
Epidemiological Evidence
What meaning does epidemiological evidence have for the individual? In evidence-based medicine, epidemiological evidence measures the patient’s risk of the outcome or the change in risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiological evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s r…
Blurred Boundaries and Strategic Surveillance
This article explores how models of architecture, surveillance, and ownership define commercialised spaces, and in turn dictate how these spaces are experienced – not only by their users but also by the ethnographer. I argue that the supposedly inclusive and open design of Cabot Circus in the city centre of Bristol, UK, has resulted in a privatised, impersonal and exclusionary shopping centre. Its mode of operation and regulation threatens to enc…
The Confounding Question of Confounding Causes in Randomized Trials
It is sometimes thought that randomized study group allocation is uniquely proficient at producing comparison groups that are evenly balanced for all confounding causes. Philosophers have argued that in real randomized controlled trials this balance assumption typically fails. But is the balance assumption an important ideal? I run a thought experiment, the CONFOUND study, to answer this question. I then suggest a new account of causal inference …
What are chronic diseases
Meta-Research Evidence for Evaluating Therapies
The new field of meta-research investigates industry bias, publication bias, contradictions between studies, and other trends in medical research. I argue that its findings should be used as meta-evidence for evaluating therapies. ‘Meta-evidence’ is evidence about the support that direct ‘first-order evidence’ provides the hypothesis. I consider three objections to my proposal: the irrelevance objection, the screening-off objection, and the under…
Universal etiology, multifactorial diseases and the constitutive model of disease classification
Prediction in epidemiology and medicine
The Risk GP Model
The Risk GP Model
The Confounding Question of Confounding Causes in Randomized Trials
It is sometimes thought that randomized study group allocation is uniquely proficient at producing comparison groups that are evenly balanced for all confounding causes. Philosophers have argued that in real randomized controlled trials this balance assumption typically fails. But is the balance assumption an important ideal? I run a thought experiment, the CONFOUND study, to answer this question. I then suggest a new account of causal inference …
What are chronic diseases
Universal etiology, multifactorial diseases and the constitutive model of disease classification
What are the Covid-19 models modeling (philosophically speaking)
The myth and fallacy of simple extrapolation in medicine
Epidemiological Evidence
What meaning does epidemiological evidence have for the individual? In evidence-based medicine, epidemiological evidence measures the patient’s risk of the outcome or the change in risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiological evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s r…
Meta-Research Evidence for Evaluating Therapies
The new field of meta-research investigates industry bias, publication bias, contradictions between studies, and other trends in medical research. I argue that its findings should be used as meta-evidence for evaluating therapies. ‘Meta-evidence’ is evidence about the support that direct ‘first-order evidence’ provides the hypothesis. I consider three objections to my proposal: the irrelevance objection, the screening-off objection, and the under…
Conceptual lessons for containing an epidemic of questionable Covid-19 counterfactual comparisons
The COVID-19 pandemic has provided limitless opportunities to compare pandemic policies across countries and over time. When the aim is to assess the comparative success of these policies, the comparison requires thinking counterfactually about ‘what would have been’ in some unrealised hypothetical (counterfactual) scenario. Whether generating modelling projections,1 making data-driven comparisons across countries2 or attributing excess harms,3 c…
Prediction in epidemiology and medicine
The Risk GP Model
Universal etiology, multifactorial diseases and the constitutive model of disease classification
What are chronic diseases
Meta-Research Evidence for Evaluating Therapies
The new field of meta-research investigates industry bias, publication bias, contradictions between studies, and other trends in medical research. I argue that its findings should be used as meta-evidence for evaluating therapies. ‘Meta-evidence’ is evidence about the support that direct ‘first-order evidence’ provides the hypothesis. I consider three objections to my proposal: the irrelevance objection, the screening-off objection, and the under…
Blurred Boundaries and Strategic Surveillance
This article explores how models of architecture, surveillance, and ownership define commercialised spaces, and in turn dictate how these spaces are experienced – not only by their users but also by the ethnographer. I argue that the supposedly inclusive and open design of Cabot Circus in the city centre of Bristol, UK, has resulted in a privatised, impersonal and exclusionary shopping centre. Its mode of operation and regulation threatens to enc…
The Confounding Question of Confounding Causes in Randomized Trials
It is sometimes thought that randomized study group allocation is uniquely proficient at producing comparison groups that are evenly balanced for all confounding causes. Philosophers have argued that in real randomized controlled trials this balance assumption typically fails. But is the balance assumption an important ideal? I run a thought experiment, the CONFOUND study, to answer this question. I then suggest a new account of causal inference …
Choosing Words Wisely
PURPOSE: To characterize how residents employ rhetorical appeals (i.e., the strategic use of communication to achieve specifiable goals) when discussing unnecessary diagnostic tests with patients. METHOD: In 2015, senior hematology residents from 10 Canadian universities participating in a national formative objective structured clinical examination (OSCE) completed a resource stewardship communication station. In this communication scenario, a s…
Book Forum
Epidemiological Evidence
What meaning does epidemiological evidence have for the individual? In evidence-based medicine, epidemiological evidence measures the patient’s risk of the outcome or the change in risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiological evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s r…
What are the Covid-19 models modeling (philosophically speaking)
Conceptual lessons for containing an epidemic of questionable Covid-19 counterfactual comparisons
The COVID-19 pandemic has provided limitless opportunities to compare pandemic policies across countries and over time. When the aim is to assess the comparative success of these policies, the comparison requires thinking counterfactually about ‘what would have been’ in some unrealised hypothetical (counterfactual) scenario. Whether generating modelling projections,1 making data-driven comparisons across countries2 or attributing excess harms,3 c…
The myth and fallacy of simple extrapolation in medicine
Preventive and curative medical interventions
Epidemics from the Population Perspective
Many epidemics consist in individuals spreading infection to others. From the population perspective, they also have population characteristics important in modeling, explaining, and intervening in epidemics. I analyze epidemiology’s contemporary population perspective through the example of epidemics by examining two central principles attributed to Geoffrey Rose: a distinction between the causes of cases and the causes of incidence, and between…
Demarcating scientific medicine
Scientific medicine and homeopathy are interesting case studies for the ongoing project of demarcating science from pseudoscience. Much of the demarcation literature formulates abstract criteria for demarcating science from pseudoscience generally. In service of a more localist approach to the demarcation problem, I reconstruct a specific demarcating difference, the like comparison criterion, invoked by nineteenth century adherents to an early mo…
Magic bullet or marginal bet—does precision medicine offer the best hope for sick individuals and sick populations
By targeting treatment according to molecular biomarkers, precision medicine promises a revolution in healthcare. We examine this promise by distinguishing three precision medicine strategies: biomarker-stratified-high-risk-targeting, biomarker-based-individual-targeting, and biomarker-based-disease-targeting. Each strategy seeks to boost one of the determinants of the population impact of a medical intervention. We conclude that these strategies…
Medicine (12 works) · Epistemology (10 works) · Psychology (9 works) · Philosophy (8 works) · Computer Science (7 works) · Pathology (6 works) · Philosophy and History of Science (5 works) · Health Systems, Economic Evaluations, Quality of Life (4 works) · Healthcare cost, quality, practices (4 works) · Philosophy of science (4 works)