Experimental effects and causal representations

In experimental settings, scientists often “make” new things, in which case the aim is to intervene in order to produce experimental objects and processes—characterized as ‘effects’. In this discussion, I illuminate an important performative function in measurement and experimentation in general: intervention-based experimental production (IEP). I argue that even though the goal of IEP is the production of new effects, it can be informative for causal details in scientific representations. Specifically, IEP can be informative about causal relations in: regularities under study; ‘intervention systems’, which are measurement/experimental systems; and new technological systems

Methodology at the Intersection between Intervention and Representation

I show that in complex methodological contexts, representational and intervention-based roles require re-conceptualization. I analyze the relations between representation and intervention by focusing on the role of intervention in mediating representations. To do this, first I show how applied scientific practice challenges the simple distinction between representational and intervention-based roles of experiment/measurement. Then I discuss the complex interaction between representation and intervention applied to methodology in biomarker measurement

Methodology at the Intersection between Intervention and Representation

I show that in complex methodological contexts, representational and intervention-based roles require re-conceptualization. I analyze the relations between representation and intervention by focusing on the role of intervention in mediating representations. To do this, first I show how applied scientific practice challenges the simple distinction between representational and intervention-based roles of experiment/measurement. Then I discuss the complex interaction between representation and intervention applied to methodology in biomarker measurement

Methodology at the Intersection between Intervention and Representation

I show that in complex methodological contexts, representational and intervention-based roles require re-conceptualization. I analyze the relations between representation and intervention by focusing on the role of intervention in mediating representations. To do this, first I show how applied scientific practice challenges the simple distinction between representational and intervention-based roles of experiment/measurement. Then I discuss the complex interaction between representation and intervention applied to methodology in biomarker measurement

Effects and Artifacts: Robustness Analysis and the Production Process

Scientists often use multiple independent methods of identification to distinguish reliable results from those produced in error (artifacts). This process is referred to as ‘robustness analysis’. I argue that even though robustness analysis is useful for differentiating natural phenomena from artifacts, it fails to differentiate experimentally produced effects from artifacts. I argue that to bypass this problem, we can re-frame the role of robustness analysis to focus on cross-comparison between methods of production. Focusing on the production relation provides information about how changes in conditions alter given effects, without first having to make a distinction between effect and artifact

Effects and Artifacts: Robustness Analysis and the Production Process

Scientists often use multiple independent methods of identification to distinguish reliable results from those produced in error (artifacts). This process is referred to as ‘robustness analysis’. I argue that even though robustness analysis is useful for differentiating natural phenomena from artifacts, it fails to differentiate experimentally produced effects from artifacts. I argue that to bypass this problem, we can re-frame the role of robustness analysis to focus on cross-comparison between methods of production. Focusing on the production relation provides information about how changes in conditions alter given effects, without first having to make a distinction between effect and artifact