Nanci Weinberger
Dados Biográficos
| ID | 145387 |
|---|---|
| NOME | Nanci Weinberger |
| PRENOMES | Nanci |
| SOBRENOME | Weinberger |
| ASSINATURA | WEINBERGER N |
| AFILIAÇÕES | Munich School of Philosophy |
| ORCID | 0000-0002-4011-5756 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 15 |
| TOTAL DE CITAÇÕES | 11 |
| TOTAL COMO AUTOR | 15 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1999 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2024 |
| ÍNDICE H | 2 |
The Insufficiency of Statistics for Detecting Racial Discrimination by Police
Benchmark tests are employed when testing for racial discrimination by police. Neil and Winship (2019) emphasize that such tests are threatened by Simpson’s paradox, but they avoid analyzing the paradox causally. They consequently cannot elucidate the link between statistical quantities and discrimination hypotheses. Simpson’s paradox reveals that the statistics given by benchmark tests are not invariant to conditioning on additional variables. O…
The Worldly Infrastructure of Causation
This paper describes an alternative to currently dominant philosophical approaches to the metaphysics of causation. It is motivated by the gap that currently exists between metaphysical accounts and recent epistemological research on causal reasoning and methods for discovering causal relationships. Our approach aims at characterizing structural features of the actual world that support, and are exploited by, successful strategies for causal reas…
Signal Manipulation and the Causal Analysis of Racial Discrimination
Discussions of the causal status of race focus on the question of whether race itself can be experimentally manipulated. Yet many experiments testing for racial discrimination do not manipulate race, but rather a signal by which race influences an outcome. Such signal manipulations are easily formalized, though contexts of discrimination introduce significant philosophical complications. Whether a signal counts as a signal for race is not merely …
Comparing Rubin and Pearl’s causal modelling frameworks
Markus (2021) argues that the causal modelling frameworks of Pearl and Rubin are not ‘strongly equivalent’, in the sense of saying ‘the same thing in different ways’. Here I rebut Markus’ arguments against strong equivalence. The differences between the frameworks are best illuminated not by appeal to their causal semantics, but rather reflect pragmatic modelling choices
Intervening and Letting Go
Causal representations are distinguished from non-causal ones by their ability to predict the results of interventions. This widely-accepted view suggests the following adequacy condition for causal models: a causal model is adequate only if it does not contain variables regarding which it makes systematically false predictions about the results of interventions. Here I argue that this condition should be rejected. For a class of equilibrium syst…
Static-Dynamic Hybridity in Dynamical Models of Cognition
Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representati…
You′re brave, I′ll be your friend
The focus of this study was to explore children's evaluations of healthy peers and peers with cancer. A racially and ethnically diverse group of fourth‐ and fifth‐grade children ( n = 109) viewed a story about a child engaged in a physically challenging rock climbing tower activity at camp. The way the child (healthy or with cancer) ascended and descended the climbing tower (independently or with assistance) was manipulated. Assessment from the p…
Near-Decomposability and the Timescale Relativity of Causal Representations
A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representati…
Mechanisms without mechanistic explanation
Some recent accounts of constitutive relevance have identified mechanism components with entities that are causal intermediaries between the input and output of a mechanism. I argue that on such accounts there is no distinctive inter-level form of mechanistic explanation and that this highlights an absence in the literature of a compelling argument that there are such explanations. Nevertheless, the entities that these accounts call ‘components’ …
Path-Specific Effects
A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1976]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on (Pearl [2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were it to be transmitted only via P. Fa…
The Frugal Inference of Causal Relations
Recent approaches to causal modelling rely upon the causal Markov condition, which specifies which probability distributions are compatible with a directed acyclic graph (DAG). Further principles are required in order to choose among the large number of DAGs compatible with a given probability distribution. Here we present a principle that we call frugality. This principle tells one to choose the DAG with the fewest causal arrows. We argue that f…
If intelligence is a cause, it is a within-subjects cause
Borsboom, Mellenbergh, and van Heerden argue that latent variables such as intelligence should be given a between-subjects causal interpretation, but not a within-subjects causal interpretation. That is, while intelligence is a cause of one subject’s doing better than another on an IQ test, there is no non-comparative sense in which intelligence – as standardly measured – is a cause of an individual’s performance. Here I expand upon Pearl’s discu…
Systems without a graphical causal representation
Is There an Empirical Disagreement between Genic and Genotypic Selection Models? A Response to Brandon and Nijhout
In a recent paper, Brandon and Nijhout argue against genic selectionism—the thesis, roughly, that evolutionary processes are best understood from the gene's-eye point of view—by presenting a case in which genic models of selection allegedly make predictions that conflict with the (correct) predictions of higher-level genotypic selection models. Their argument, if successful, would refute the widely held belief that genic models and higher-level m…
Assessing Object Mastery in the Home
In this study, the causal relationship between introduced noise and object clutter on infant performance was tested empirically. The infants were studied in their own homes and they actively engaged with the test materials, demonstrating object mastery. Surprisingly, however, the noise and object clutter did not interfere with the quality of object mastery for these twelve month olds. The differences between home and laboratory testing, as well a…
Near-Decomposability and the Timescale Relativity of Causal Representations
A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representati…
The Frugal Inference of Causal Relations
Recent approaches to causal modelling rely upon the causal Markov condition, which specifies which probability distributions are compatible with a directed acyclic graph (DAG). Further principles are required in order to choose among the large number of DAGs compatible with a given probability distribution. Here we present a principle that we call frugality. This principle tells one to choose the DAG with the fewest causal arrows. We argue that f…
Mechanisms without mechanistic explanation
Some recent accounts of constitutive relevance have identified mechanism components with entities that are causal intermediaries between the input and output of a mechanism. I argue that on such accounts there is no distinctive inter-level form of mechanistic explanation and that this highlights an absence in the literature of a compelling argument that there are such explanations. Nevertheless, the entities that these accounts call ‘components’ …
The Worldly Infrastructure of Causation
This paper describes an alternative to currently dominant philosophical approaches to the metaphysics of causation. It is motivated by the gap that currently exists between metaphysical accounts and recent epistemological research on causal reasoning and methods for discovering causal relationships. Our approach aims at characterizing structural features of the actual world that support, and are exploited by, successful strategies for causal reas…
Path-Specific Effects
A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1976]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on (Pearl [2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were it to be transmitted only via P. Fa…
Systems without a graphical causal representation
Assessing Object Mastery in the Home
In this study, the causal relationship between introduced noise and object clutter on infant performance was tested empirically. The infants were studied in their own homes and they actively engaged with the test materials, demonstrating object mastery. Surprisingly, however, the noise and object clutter did not interfere with the quality of object mastery for these twelve month olds. The differences between home and laboratory testing, as well a…
Is There an Empirical Disagreement between Genic and Genotypic Selection Models? A Response to Brandon and Nijhout
In a recent paper, Brandon and Nijhout argue against genic selectionism—the thesis, roughly, that evolutionary processes are best understood from the gene's-eye point of view—by presenting a case in which genic models of selection allegedly make predictions that conflict with the (correct) predictions of higher-level genotypic selection models. Their argument, if successful, would refute the widely held belief that genic models and higher-level m…
Systems without a graphical causal representation
If intelligence is a cause, it is a within-subjects cause
Borsboom, Mellenbergh, and van Heerden argue that latent variables such as intelligence should be given a between-subjects causal interpretation, but not a within-subjects causal interpretation. That is, while intelligence is a cause of one subject’s doing better than another on an IQ test, there is no non-comparative sense in which intelligence – as standardly measured – is a cause of an individual’s performance. Here I expand upon Pearl’s discu…
The Frugal Inference of Causal Relations
Recent approaches to causal modelling rely upon the causal Markov condition, which specifies which probability distributions are compatible with a directed acyclic graph (DAG). Further principles are required in order to choose among the large number of DAGs compatible with a given probability distribution. Here we present a principle that we call frugality. This principle tells one to choose the DAG with the fewest causal arrows. We argue that f…
Mechanisms without mechanistic explanation
Some recent accounts of constitutive relevance have identified mechanism components with entities that are causal intermediaries between the input and output of a mechanism. I argue that on such accounts there is no distinctive inter-level form of mechanistic explanation and that this highlights an absence in the literature of a compelling argument that there are such explanations. Nevertheless, the entities that these accounts call ‘components’ …
Path-Specific Effects
A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1976]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on (Pearl [2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were it to be transmitted only via P. Fa…
Near-Decomposability and the Timescale Relativity of Causal Representations
A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representati…
You′re brave, I′ll be your friend
The focus of this study was to explore children's evaluations of healthy peers and peers with cancer. A racially and ethnically diverse group of fourth‐ and fifth‐grade children ( n = 109) viewed a story about a child engaged in a physically challenging rock climbing tower activity at camp. The way the child (healthy or with cancer) ascended and descended the climbing tower (independently or with assistance) was manipulated. Assessment from the p…
Static-Dynamic Hybridity in Dynamical Models of Cognition
Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representati…
Signal Manipulation and the Causal Analysis of Racial Discrimination
Discussions of the causal status of race focus on the question of whether race itself can be experimentally manipulated. Yet many experiments testing for racial discrimination do not manipulate race, but rather a signal by which race influences an outcome. Such signal manipulations are easily formalized, though contexts of discrimination introduce significant philosophical complications. Whether a signal counts as a signal for race is not merely …
Comparing Rubin and Pearl’s causal modelling frameworks
Markus (2021) argues that the causal modelling frameworks of Pearl and Rubin are not ‘strongly equivalent’, in the sense of saying ‘the same thing in different ways’. Here I rebut Markus’ arguments against strong equivalence. The differences between the frameworks are best illuminated not by appeal to their causal semantics, but rather reflect pragmatic modelling choices
Intervening and Letting Go
Causal representations are distinguished from non-causal ones by their ability to predict the results of interventions. This widely-accepted view suggests the following adequacy condition for causal models: a causal model is adequate only if it does not contain variables regarding which it makes systematically false predictions about the results of interventions. Here I argue that this condition should be rejected. For a class of equilibrium syst…
The Insufficiency of Statistics for Detecting Racial Discrimination by Police
Benchmark tests are employed when testing for racial discrimination by police. Neil and Winship (2019) emphasize that such tests are threatened by Simpson’s paradox, but they avoid analyzing the paradox causally. They consequently cannot elucidate the link between statistical quantities and discrimination hypotheses. Simpson’s paradox reveals that the statistics given by benchmark tests are not invariant to conditioning on additional variables. O…
The Worldly Infrastructure of Causation
This paper describes an alternative to currently dominant philosophical approaches to the metaphysics of causation. It is motivated by the gap that currently exists between metaphysical accounts and recent epistemological research on causal reasoning and methods for discovering causal relationships. Our approach aims at characterizing structural features of the actual world that support, and are exploited by, successful strategies for causal reas…
Computer Science (11 obras) · Epistemology (8 obras) · Mathematics (8 obras) · Philosophy and History of Science (8 obras) · Psychology (8 obras) · Philosophy (7 obras) · Bayesian Modeling and Causal Inference (6 obras) · Causal model (6 obras) · Econometrics (6 obras) · Statistics (6 obras)