scholarly journals Norms Affect Prospective Causal Judgments

2019 ◽  
Author(s):  
Paul Henne ◽  
Kevin O'Neill ◽  
Paul Bello ◽  
Sangeet Khemlani ◽  
Felipe De Brigard
Keyword(s):  
Selection Effect ◽  
Causal Judgment ◽  
Selection Effects ◽  
Causal Judgments

People more frequently select norm-violating factors, relative to norm-conforming ones, as the cause of some outcome. Until recently, this abnormal-selection effect has been studied using retrospective vignette-based paradigms. We use a novel set of video stimuli to investigate this effect for prospective causal judgments—i.e., judgments about the cause of some future outcome. Four experiments show that people more frequently select norm-violating factors, relative to norm-conforming ones, as the cause of some future outcome. We show that the abnormal-selection effects are not primarily explained by the perception of agency (Experiment 4). We discuss these results in relation to recent efforts to model causal judgment.

scholarly journals Social Media Use and Support for Populist Radical Right Parties: Assessing Exposure and Selection Effects in a Two-wave Panel Study

2019 ◽  
Author(s):  
Sandy Schumann ◽  
Diana Boer ◽  
Katja Hanke ◽  
James H Liu
Keyword(s):  
Social Media ◽  
Media Use ◽  
Panel Study ◽  
Selection Effect ◽  
Radical Right ◽  
Survey Study ◽  
Selection Effects ◽  
Social Media Use ◽  
Populist Radical Right ◽  
Radical Right Parties

Vote shares for populist radical right parties (PRRPs) have increased considerably in recent years, and this advancement of PRRPs has been attributed in part to social media. We assess the affinity between social media and populist radical right parties by examining whether more frequent social media use for news enhances the willingness to vote for a PRRP (exposure effect) as well as whether individuals who have voted for a PRRP in the past use social media more frequently to access news (selection effect). To address these research questions, we analysed data of a two-wave survey study that was conducted in Germany, focusing on the party Alternative for Germany (AfD). Binary logistic regression highlighted that social media use increased the likelihood of supporting the AfD. Pre-registered multinominal analyses, however, showed that this effect was driven by specific party comparisons. That is, using the AfD as a reference category, social media use reduced intentions to vote for parties that expressed similar positions as the AfD on the issue of immigration and with which the PRRP competes over votes. Social media selection effects were not supported.

Online protest participation and the digital divide: Modeling the effect of the digital divide on online petition-signing

2016 ◽  
Vol 20 (2) ◽  
pp. 698-719 ◽  
Author(s):  
Thomas Elliott ◽  
Jennifer Earl
Keyword(s):  
Middle Class ◽  
Digital Divide ◽  
Selection Effect ◽  
Internet Access ◽  
Selection Effects ◽  
Heckman Model ◽  
Disadvantaged Groups ◽  
Digital Divides ◽  
Online Activism ◽  
Main Effects

Scholars have long been concerned about the effect that digital inequalities might have on marginalized populations. Concern for the “digital divide” extends to social movement scholars, who worry that the digital divide will lead to social movements privileging the concerns of the middle class over those of disadvantaged groups. We argue for a novel way of testing for such effects—the use of a Heckman regression model to model participation in online activism. The Heckman model separately models selection effects (i.e. first-level digital divides that affect Internet access) and main effects (i.e. second-level digital divides and classic predictors of micro-mobilization). We find that the digital divide in access does not exert a selection effect and that the digital divide in usage exerts minimal effects in models predicting online petition-signing.

Rules of Causal Judgment

2017 ◽  
Author(s):  
José C. Perales ◽  
Andrés Catena ◽  
Antonio Cándido ◽  
Antonio Maldonado
Keyword(s):  
Real Life ◽  
Statistical Information ◽  
Causal Judgment ◽  
Psychological Processes ◽  
Relevant Evidence ◽  
Clear Winner ◽  
Causal Judgments ◽  
The Media

Our environment is rich in statistical information. Frequencies and proportions—or their visual depictions—are pervasive in the media, and frequently used to support or weaken causal statements, or to bias people’s beliefs in a given direction. The topic of this chapter is how people integrate naturally available frequencies and probabilities into judgments of the strength of the link between a candidate cause and an effect. We review studies investigating various rules that have been claimed to underlie intuitive causal judgments. Given that none of these rules has been established as a clear winner, we conclude presenting a tentative framework describing the general psychological processes operating when people select, ponder, and integrate pieces of causally-relevant evidence with the goal of meeting real-life demands.

scholarly journals A Counterfactual Explanation for the Action Effect

2019 ◽  
Author(s):  
Paul Henne ◽  
Laura Niemi ◽  
Angel Pinillos ◽  
Felipe De Brigard ◽  
Joshua Knobe
Keyword(s):  
Causal Judgment ◽  
Action Effect ◽  
Original Action ◽  
Causal Judgments

People’s causal judgments are susceptible to the action effect, whereby they judge actions to be more causal than inactions. We offer a new explanation for this effect, the counterfactual explanation: people judge actions to be more causal than inactions because they are more inclined to consider the counterfactual alternatives to actions than to consider counterfactual alternatives to inactions. Experiment 1a conceptually replicates the original action effect for causal judgments. Experiment 1b confirms a novel prediction of the new explanation, the reverse action effect, in which people judge inactions to be more causal than actions in overdetermination cases. Experiment 2 directly compares the two effects in joint-causation and overdetermination scenarios and conceptually replicates them with new scenarios. Taken together, these studies provide support for the new counterfactual explanation for the action effect in causal judgment.

Some selection effects in the discovery of AAA's and their influences on their q and Ω distributions

1999 ◽  
Vol 173 ◽  
pp. 115-120
Author(s):  
E. Kostolanský
Keyword(s):  
Selection Effect ◽  
Selection Effects ◽  
The Earth ◽  
Autumnal Equinox

AbstractTheqand Ω distributions of the Amor–Apollo–Aten (AAA) asteroids indicate the existence of some selection effects of their discoveries. In the case of theqdistribution the problem of persistence of an asteroid near the Earth is decisive. The persistence of asteroids withq< 1 AU anda> 1 AU near the Earth is roughly ∼vg−1(vgis the geocentric velocity of an asteroid near the Earth). Functionvg−1(q) is discussed for orbits withi= 0° anda =1.1, 1.5, 2.0 and 2.5 AU, which are typical values ofafor the AAA asteroids. For asteroids withq> 1 AU the problem of persistence of an asteroid near opposition is decisive. The optimum orbits (the longest persistance of an asteroid near the opposition) withq[AU] = (1 +e)⅓,i= 0° are discussed. The Ω distribution is probably influenced by a large amount of minor selection effects. One of them might be based on fact that on vernal or autumnal equinox all asteroids with Ω ≈ 180° andi≈ 23.5° have declinationδ≈ 0°, hence it is easy to observe them in these periods of the year. This selection effect is discussed in detail also with its observational consequences.

scholarly journals An interaction effect of norm violations on causal judgment

2021 ◽  
Author(s):  
Maureen Gill ◽  
Jonathan F. Kominsky ◽  
Thomas Icard ◽  
Joshua Knobe
Keyword(s):  
Interaction Effect ◽  
Causal Judgment ◽  
Interaction Pattern ◽  
Moral Norms ◽  
Norm Violations ◽  
Proper Functioning ◽  
Causal Judgments ◽  
Robust Evidence

Existing research has shown that norm violations influence causal judgments, and a number of different models have been developed to explain these effects. One such model, the necessity/sufficiency model, predicts an interaction pattern in people's judgments. Specifically, it predicts that when people are judging the degree to which a particular factor is a cause, there should be an interaction between (a) the degree to which that factor violates a norm and (b) the degree to which another factor in the situation violates norms. A study of moral norms (N = 1000) and norms of proper functioning (N = 3000) revealed robust evidence for the predicted interaction effect. The implications of these patterns for existing theories of causal judgments is discussed.

scholarly journals Quantitative causal selection patterns in token causation

2019 ◽  
Author(s):  
Adam Morris ◽  
Jonathan Scott Phillips ◽  
Tobias Gerstenberg ◽  
Fiery Andrews Cushman
Keyword(s):  
Good Reason ◽  
Causal Judgment ◽  
Lightning Strike ◽  
Lightning Strikes ◽  
Prior Probabilities ◽  
Causal Judgments ◽  
Causal Selection

When many events contributed to an outcome, people consistently judge some more causal than others, based in part on the prior probabilities of those events. For instance, when a tree bursts into flames, people judge the lightning strike more of a cause than the presence of oxygen in the air -- in part because oxygen is so common, and lightning strikes are so rare. These effects, which play a major role in several prominent theories of token causation, have largely been studied through qualitative manipulations of the prior probabilities. Yet, there is good reason to think that people's causal judgments are on a continuum -- and relatively little is known about how these judgments vary quantitatively as the prior probabilities change. In this paper, we measure people's causal judgment across parametric manipulations of the prior probabilities of antecedent events. Our experiments replicate previous qualitative findings, and also reveal several novel patterns that are not well-described by existing theories.

scholarly journals A counterfactual simulation model of causal judgment

2020 ◽  
Author(s):  
Tobias Gerstenberg ◽  
Noah D. Goodman ◽  
David Lagnado ◽  
Joshua Tenenbaum
Keyword(s):  
Simulation Model ◽  
Causal Judgment ◽  
Physical Domain ◽  
Heuristic Model ◽  
Physical Support ◽  
Quantitative Mapping ◽  
Causal Judgments ◽  
Counterfactual Simulation

How do people make causal judgments? We introduce the counterfactual simulation model (CSM) which predicts causal judgments by comparing what actually happened with what would have happened in relevant counterfactual situations. The CSM postulates different aspects of causation that capture the extent to which a cause made a difference to whether and how the outcome occurred, and whether the cause was sufficient and robust. We test the CSM in three experiments in which participants make causal judgments about dynamic collision events. Experiment 1 establishes a very close quantitative mapping between causal judgments and counterfactual simulations. Experiment 2 demonstrates that counterfactuals are necessary for explaining causal judgments. Participants' judgments differed dramatically between pairs of situations in which what actually happened was identical, but where what would have happened differed. Experiment 3 features two candidate causes and shows that participants' judgments are sensitive to different aspects of causation. The CSM provides a better fit to participants' judgments than a heuristic model which uses features based on what actually happened. We discuss how the CSM can be used to model the semantics of different causal verbs, how it captures related concepts such as physical support, and how its predictions extend beyond the physical domain.

The Secret Success of Nonproliferation Sanctions

2014 ◽  
Vol 68 (4) ◽  
pp. 913-944 ◽  
Author(s):  
Nicholas L. Miller
Keyword(s):  
United States ◽  
Statistical Analysis ◽  
Qualitative Analysis ◽  
Nuclear Weapons ◽  
Selection Effect ◽  
Original Data ◽  
The United States ◽  
Selection Effects ◽  
Data Set ◽  
South Korean

AbstractBuilding on the rationalist literature on sanctions, this article argues that economic and political sanctions are a successful tool of nonproliferation policy, but that selection effects have rendered this success largely hidden. Since the late 1970s—when the United States made the threat of sanctions credible through congressional legislation and began regularly employing sanctions against proliferating states—sanctions have been ineffective in halting ongoing nuclear weapons programs, but they have succeeded in deterring states from starting nuclear weapons programs in the first place and have thus contributed to a decline in the rate of nuclear pursuit. The logic of the argument is simple: rational leaders assess the risk of sanctions before initiating a nuclear weapons program, which produces a selection effect whereby states highly vulnerable to sanctions are deterred from starting nuclear weapons programs in the first place, so long as the threat is credible. Vulnerability is a function of a state's level of economic and security dependence on the United States—states with greater dependence have more to lose from US sanctions and are more likely to be sensitive to US-sponsored norms. The end result of this selection effect is that since the late 1970s, only insulated, inward-looking regimes have pursued nuclear weapons and become the target of imposed sanctions, thus rendering the observed success rate of nonproliferation sanctions low. I find support for the argument based on statistical analysis of a global sample of countries from 1950 to 2000, an original data set of US nonproliferation sanctions episodes, and qualitative analysis of the South Korean and Taiwanese nuclear weapons programs.

scholarly journals Certainty and Singular Causal Judgment

2021 ◽  
Author(s):  
Kevin O'Neill
Keyword(s):  
Decision Making ◽  
Causal Judgment ◽  
Metacognitive Judgments ◽  
Formal Framework ◽  
Wide Range ◽  
Causal Judgments ◽  
Causal Strength

In this paper, I map out broad aims, challenges, predictions, and implica- tions for the resulting intersection of singular causal judgment and metacognition that I (tentatively) call causal metacognition. First, I will overview research on sin- gular causal judgment, focusing on popular counterfactual theories that provide a formal framework for evaluating dependency relationships, as well as several compet- ing definitions of singular causal strength. Next, I will provide relevant background in the literature on metacognition for perception and decision-making, discussing major computational theories of metacognitive judgments. After covering the small amount of work on uncertainty in causal judgments, I will then argue that although singular causal judgments pose a particular problem for some theories of metacognition, coun- terfactual theories of singular causal judgment already provide testable predictions for confidence in causal judgments and can be extended to account for a wide range of patterns in confidence in singular causal judgments. Finally, I will summarize why we need a study of causal metacognition, and what empirical and theoretical advancements in that field might look like.

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