Related Experiment Video
Updated: Jun 28, 2025

06:45
Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal
Published on: April 18, 2017
6.2K
Revisiting causal pluralism: Intention, process, and dependency in cases of double prevention
Huseina Thanawala1, Christopher D Erb1
1School of Psychology, University of Auckland, 23 Symonds Street, Building 302, Auckland 1010, New Zealand.
Cognition
|April 17, 2024
Summary
Causal pluralism suggests people use dependency and process reasoning for causes. New research challenges this by showing intentionality
Area of Science:
- Cognitive Science
- Psychology
- Philosophy of Mind
Background:
- Causal pluralism posits dual reasoning modes: dependency and process relations.
- Previous studies linked intentionality to differential weighting of these relations in double prevention scenarios.
- Research suggested intentional actions influence causal attributions.
Purpose of the Study:
- To challenge the causal pluralism account of intentionality's role in causal reasoning.
- To investigate if intentionality exclusively impacts dependency relation weighting.
- To explore if process relations explain double preventer attributions and the impact of action order.
Main Methods:
- Experiments 1-2: Examined intentionality's effect on dependency and process relation interpretations.
- Experiments 3-4: Manipulated action order to assess unintentional double preventer causality compared to intentional affectors.
- Utilized double prevention scenarios with varying intentionality and action sequences.
Main Results:
- Intentionality may not solely enhance dependency relation weighting.
- Evidence suggests reasoners interpret unintentional actions via process relations.
- Altering action order significantly impacted causal ratings, favoring unintentional double preventers over intentional affectors in specific contexts.
Conclusions:
- The causal pluralism account requires re-evaluation regarding intentionality's influence.
- Reasoners' interpretation of causal scenarios, especially with intentional actions, is more complex than previously assumed.
- Future research should explore the dynamic interplay of intentionality, action order, and reasoning modes in causal judgment.
More Related Videos
Related Concept Videos
Criteria for Causality: Bradford Hill Criteria - II
301
The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
301
Causality in Epidemiology
400
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
400
Criteria for Causality: Bradford Hill Criteria - I
282
The Bradford Hill criteria are a group of principles that provide a framework to determine a causal relationship between a specific factor and a disease. There are nine criteria that are pivotal in assessing causality in epidemiological studies. Here's a closer look at Strength, Consistency, Specificity, and Temporality criteria with definitions and examples:
282
Cause and Effect
10.9K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.9K
Correlation and Causation
37.6K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
37.6K
Strategies for Assessing and Addressing Confounding
95
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
95

