Jaakko Kuorikoski
Biographic Data
| ID | 389160 |
|---|---|
| NAME | Jaakko Kuorikoski |
| GIVEN NAMES | Jaakko |
| FAMILY NAME | Kuorikoski |
| SIGNATURE | KUORIKOSKI J |
| AFFILIATIONS | University of Helsinki |
| ORCID | 0000-0001-5676-717X |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 143 |
| WORKS AS AUTHOR | 19 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 7 |
Contrastive Evidence and Inductive Risk
I argue that non-epistemic values are necessarily embedded in the measure of evidential strength of contrastive evidence. When evidence is contrastive, evidence is stronger the more it favours a hypothesis over a set of plausible, mutually exclusive alternative hypotheses. In such a contrastive epistemic setting, evidence has an effect not only on a particular hypothesis, but on the whole probability distribution over the set of alternative hypot…
The logic of regulatory impact assessment
Agencies involved in generating regulatory policies promote evidence‐based regulatory impact assessments (RIAs) to improve the predictability of regulation and develop informed policy. Here, we analyze the epistemic foundations of RIAs. We frame RIA as reasoning that connects various types of knowledge to inferences about the future. Drawing on Stephen Toulmin's model of argumentation, we situate deductive and inductive reasoning steps within a s…
The division of cognitive labor and the structure of interdisciplinary problems
Interdisciplinarity is strongly promoted in science policy across the world. It is seen as a necessary condition for providing practical solutions to many pressing complex problems for which no single disciplinary approach is adequate alone. In this article we model multi- and interdisciplinary research as an instance of collective problem solving. Our goal is to provide a basic representation of this type of problem solving and chart the epistem…
Social and cognitive diversity in science
Evidential Variety and Mixed-Methods Research in Social Science
Mixed-methods research (MMR)—the combination of qualitative and quantitative data within the same design to strengthen causal inference—is gaining prominence in the social sciences but its benefits are contested. There remains confusion over which methods to mix and what is the point of mixing them. We argue that variety of evidence is what matters, not of data or methods, and that distinct epistemic principles underlie its added value for causal…
The Diversity-Ability Trade-Off in Scientific Problem Solving
According to the diversity-beats-ability theorem, groups of diverse problem solvers can outperform groups of high-ability problem solvers. We argue that the model introduced by Lu Hong and Scott Page is inadequate for exploring the trade-off between diversity and ability. This is because the model employs an impoverished implementation of the problem-solving task. We present a new version of the model that captures the role of ‘ability’ in a mean…
There Are No Mathematical Explanations
If ontic dependence is the basis of explanation, there cannot be mathematical explanations. Accounting for the explanatory dependency between mathematical properties and empirical phenomena poses insurmountable metaphysical and epistemic difficulties, and the proposed amendments to the counterfactual theory of explanation invariably violate core commitments of the theory. Instead, mathematical explanations are either abstract mechanistic constitu…
Re-socializing the Vulnerable Brain
According to the brain disease model of addiction (BDMA), substance addiction is a chronic, relapsing brain disease. The BDMA is currently influential in informing addiction policy and the development of new treatments, but remains highly controversial across the addiction research community. We draw on resources from philosophy of science and applied ethics to re-examine the methodological and ethical implications of the BDMA and offer a new for…
Evidential Diversity and the Triangulation of Phenomena
The article argues for the epistemic rationale of triangulation, namely, the use of multiple and independent sources of evidence. It claims that triangulation is to be understood as causal reasoning from data to phenomenon, and it rationalizes its epistemic value in terms of controlling for likely errors and biases of particular data-generating procedures. This perspective is employed to address objections against triangulation concerning the fal…
External representations and scientific understanding
Unification and mechanistic detail as drivers of model construction
Understanding Nonmodular Functionality
Evolution is often characterized as a tinkerer creating efficient but messy solutions. We analyze the nature of the problems that arise when trying to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem—solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational p…
How to Be a Humean Interventionist
This paper aims to provide Humean metaphysics for the interventionist theory of causation. This is done by appealing to the hierarchical picture of causal relations as being realized by mechanisms, which in turn are identified with lower‐level causal structures. The modal content of invariances at the lowest level of this hierarchy, at which mechanisms are reduced to strict natural laws, is then explained in terms of projectivism based on the bes…
Looping Kinds and Social Mechanisms
Human behavior is not always independent of the ways in which humans are scientifically classified. That there are looping effects of human kinds has been used as an argument for the methodological separation of the natural and the human sciences and to justify social constructionist claims. We suggest that these arguments rely on false presuppositions and present a mechanisms-based account of looping that provides a better way to understand the …
Dissecting explanatory power
Economics Imperialism and Solution Concepts in Political Science
Political science and economic science . . . make use of the same language, the same mode of abstraction, the same instruments of thought and the same method of reasoning. (Black 1998, 354) Proponents as well as opponents of economics imperialism agree that imperialism is a matter of unification; providing a unified framework for social scientific analysis. Uskali Mäki distinguishes between derivational and ontological unification and argues that…
Economic Modelling as Robustness Analysis
We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt’s account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial me…
Unrealistic Assumptions in Rational Choice Theory
The most common argument against the use of rational choice models outside economics is that they make unrealistic assumptions about individual behavior. We argue that whether the falsity of assumptions matters in a given model depends on which factors are explanatorily relevant. Since the explanatory factors may vary from application to application, effective criticism of economic model building should be based on model-specific arguments showin…
Computing the Perfect Model
Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The comp…
Economic Modelling as Robustness Analysis
We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt’s account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial me…
Evidential Diversity and the Triangulation of Phenomena
The article argues for the epistemic rationale of triangulation, namely, the use of multiple and independent sources of evidence. It claims that triangulation is to be understood as causal reasoning from data to phenomenon, and it rationalizes its epistemic value in terms of controlling for likely errors and biases of particular data-generating procedures. This perspective is employed to address objections against triangulation concerning the fal…
External representations and scientific understanding
Looping Kinds and Social Mechanisms
Human behavior is not always independent of the ways in which humans are scientifically classified. That there are looping effects of human kinds has been used as an argument for the methodological separation of the natural and the human sciences and to justify social constructionist claims. We suggest that these arguments rely on false presuppositions and present a mechanisms-based account of looping that provides a better way to understand the …
Unrealistic Assumptions in Rational Choice Theory
The most common argument against the use of rational choice models outside economics is that they make unrealistic assumptions about individual behavior. We argue that whether the falsity of assumptions matters in a given model depends on which factors are explanatorily relevant. Since the explanatory factors may vary from application to application, effective criticism of economic model building should be based on model-specific arguments showin…
Computing the Perfect Model
Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The comp…
The Diversity-Ability Trade-Off in Scientific Problem Solving
According to the diversity-beats-ability theorem, groups of diverse problem solvers can outperform groups of high-ability problem solvers. We argue that the model introduced by Lu Hong and Scott Page is inadequate for exploring the trade-off between diversity and ability. This is because the model employs an impoverished implementation of the problem-solving task. We present a new version of the model that captures the role of ‘ability’ in a mean…
There Are No Mathematical Explanations
If ontic dependence is the basis of explanation, there cannot be mathematical explanations. Accounting for the explanatory dependency between mathematical properties and empirical phenomena poses insurmountable metaphysical and epistemic difficulties, and the proposed amendments to the counterfactual theory of explanation invariably violate core commitments of the theory. Instead, mathematical explanations are either abstract mechanistic constitu…
Unification and mechanistic detail as drivers of model construction
Evidential Variety and Mixed-Methods Research in Social Science
Mixed-methods research (MMR)—the combination of qualitative and quantitative data within the same design to strengthen causal inference—is gaining prominence in the social sciences but its benefits are contested. There remains confusion over which methods to mix and what is the point of mixing them. We argue that variety of evidence is what matters, not of data or methods, and that distinct epistemic principles underlie its added value for causal…
How to Be a Humean Interventionist
This paper aims to provide Humean metaphysics for the interventionist theory of causation. This is done by appealing to the hierarchical picture of causal relations as being realized by mechanisms, which in turn are identified with lower‐level causal structures. The modal content of invariances at the lowest level of this hierarchy, at which mechanisms are reduced to strict natural laws, is then explained in terms of projectivism based on the bes…
Economics Imperialism and Solution Concepts in Political Science
Political science and economic science . . . make use of the same language, the same mode of abstraction, the same instruments of thought and the same method of reasoning. (Black 1998, 354) Proponents as well as opponents of economics imperialism agree that imperialism is a matter of unification; providing a unified framework for social scientific analysis. Uskali Mäki distinguishes between derivational and ontological unification and argues that…
The division of cognitive labor and the structure of interdisciplinary problems
Interdisciplinarity is strongly promoted in science policy across the world. It is seen as a necessary condition for providing practical solutions to many pressing complex problems for which no single disciplinary approach is adequate alone. In this article we model multi- and interdisciplinary research as an instance of collective problem solving. Our goal is to provide a basic representation of this type of problem solving and chart the epistem…
The logic of regulatory impact assessment
Agencies involved in generating regulatory policies promote evidence‐based regulatory impact assessments (RIAs) to improve the predictability of regulation and develop informed policy. Here, we analyze the epistemic foundations of RIAs. We frame RIA as reasoning that connects various types of knowledge to inferences about the future. Drawing on Stephen Toulmin's model of argumentation, we situate deductive and inductive reasoning steps within a s…
Understanding Nonmodular Functionality
Evolution is often characterized as a tinkerer creating efficient but messy solutions. We analyze the nature of the problems that arise when trying to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem—solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational p…
Unrealistic Assumptions in Rational Choice Theory
The most common argument against the use of rational choice models outside economics is that they make unrealistic assumptions about individual behavior. We argue that whether the falsity of assumptions matters in a given model depends on which factors are explanatorily relevant. Since the explanatory factors may vary from application to application, effective criticism of economic model building should be based on model-specific arguments showin…
Computing the Perfect Model
Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The comp…
Dissecting explanatory power
Economics Imperialism and Solution Concepts in Political Science
Political science and economic science . . . make use of the same language, the same mode of abstraction, the same instruments of thought and the same method of reasoning. (Black 1998, 354) Proponents as well as opponents of economics imperialism agree that imperialism is a matter of unification; providing a unified framework for social scientific analysis. Uskali Mäki distinguishes between derivational and ontological unification and argues that…
Economic Modelling as Robustness Analysis
We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt’s account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial me…
Looping Kinds and Social Mechanisms
Human behavior is not always independent of the ways in which humans are scientifically classified. That there are looping effects of human kinds has been used as an argument for the methodological separation of the natural and the human sciences and to justify social constructionist claims. We suggest that these arguments rely on false presuppositions and present a mechanisms-based account of looping that provides a better way to understand the …
Understanding Nonmodular Functionality
Evolution is often characterized as a tinkerer creating efficient but messy solutions. We analyze the nature of the problems that arise when trying to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem—solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational p…
How to Be a Humean Interventionist
This paper aims to provide Humean metaphysics for the interventionist theory of causation. This is done by appealing to the hierarchical picture of causal relations as being realized by mechanisms, which in turn are identified with lower‐level causal structures. The modal content of invariances at the lowest level of this hierarchy, at which mechanisms are reduced to strict natural laws, is then explained in terms of projectivism based on the bes…
Unification and mechanistic detail as drivers of model construction
External representations and scientific understanding
Evidential Diversity and the Triangulation of Phenomena
The article argues for the epistemic rationale of triangulation, namely, the use of multiple and independent sources of evidence. It claims that triangulation is to be understood as causal reasoning from data to phenomenon, and it rationalizes its epistemic value in terms of controlling for likely errors and biases of particular data-generating procedures. This perspective is employed to address objections against triangulation concerning the fal…
Re-socializing the Vulnerable Brain
According to the brain disease model of addiction (BDMA), substance addiction is a chronic, relapsing brain disease. The BDMA is currently influential in informing addiction policy and the development of new treatments, but remains highly controversial across the addiction research community. We draw on resources from philosophy of science and applied ethics to re-examine the methodological and ethical implications of the BDMA and offer a new for…
The Diversity-Ability Trade-Off in Scientific Problem Solving
According to the diversity-beats-ability theorem, groups of diverse problem solvers can outperform groups of high-ability problem solvers. We argue that the model introduced by Lu Hong and Scott Page is inadequate for exploring the trade-off between diversity and ability. This is because the model employs an impoverished implementation of the problem-solving task. We present a new version of the model that captures the role of ‘ability’ in a mean…
There Are No Mathematical Explanations
If ontic dependence is the basis of explanation, there cannot be mathematical explanations. Accounting for the explanatory dependency between mathematical properties and empirical phenomena poses insurmountable metaphysical and epistemic difficulties, and the proposed amendments to the counterfactual theory of explanation invariably violate core commitments of the theory. Instead, mathematical explanations are either abstract mechanistic constitu…
The logic of regulatory impact assessment
Agencies involved in generating regulatory policies promote evidence‐based regulatory impact assessments (RIAs) to improve the predictability of regulation and develop informed policy. Here, we analyze the epistemic foundations of RIAs. We frame RIA as reasoning that connects various types of knowledge to inferences about the future. Drawing on Stephen Toulmin's model of argumentation, we situate deductive and inductive reasoning steps within a s…
The division of cognitive labor and the structure of interdisciplinary problems
Interdisciplinarity is strongly promoted in science policy across the world. It is seen as a necessary condition for providing practical solutions to many pressing complex problems for which no single disciplinary approach is adequate alone. In this article we model multi- and interdisciplinary research as an instance of collective problem solving. Our goal is to provide a basic representation of this type of problem solving and chart the epistem…
Social and cognitive diversity in science
Evidential Variety and Mixed-Methods Research in Social Science
Mixed-methods research (MMR)—the combination of qualitative and quantitative data within the same design to strengthen causal inference—is gaining prominence in the social sciences but its benefits are contested. There remains confusion over which methods to mix and what is the point of mixing them. We argue that variety of evidence is what matters, not of data or methods, and that distinct epistemic principles underlie its added value for causal…
Contrastive Evidence and Inductive Risk
I argue that non-epistemic values are necessarily embedded in the measure of evidential strength of contrastive evidence. When evidence is contrastive, evidence is stronger the more it favours a hypothesis over a set of plausible, mutually exclusive alternative hypotheses. In such a contrastive epistemic setting, evidence has an effect not only on a particular hypothesis, but on the whole probability distribution over the set of alternative hypot…
Epistemology (16 works) · Computer Science (13 works) · Philosophy (13 works) · Economics (10 works) · Sociology (9 works) · Philosophy and History of Science (8 works) · Psychology (8 works) · Law (6 works) · Mathematics (6 works) · Metaphysics (6 works)