Worry in Adults and Children: Developmental Differences in the Importance of Probability and Cost Judgments

This study investigated developmental differences in the relationship of probability and cost estimates to worrying. Adults, younger children (M age = 8.67 years) and older children (M age = 11.06 years) rated the extent to which they worry about a list of negative social and physical outcomes and provided subjective probability and cost estimates for the same outcomes. Adults reported worrying more about social outcomes and rated them as less ‘bad’ (or costly) but more likely to occur than physical outcomes. Unlike adults, children in both age groups reported worrying more about physical outcomes. However, similar to adults, they also rated social outcomes as less ‘bad’ but more likely to occur than physical outcomes. Regression analyses showed that probability ratings were the best predictors of worry in adults, both probability and cost ratings equally predicted worry in older children, but only cost ratings predicted worry in younger children.

What determines biological fitness? The problem of the reference environment

Organisms’ environments are thought to play a fundamental role in determining their fitness and hence in natural selection. Existing intuitive conceptions of environment are sufficient for biological practice. I argue, however, that attempts to produce a general characterization of fitness and natural selection are incomplete without the help of general conceptions of what conditions are included in the environment. Thus there is a “problem of the reference environment”—more particularly, problems of specifying principles which pick out those environmental conditions which determine fitness. I distinguish various reference environment problems and propose solutions to some of them. While there has been a limited amount of work on problems concerning what I call “subenvironments”, there appears to be no earlier work on problems of what I call the “whole environment”. The first solution I propose for a whole environment problem specifies the overall environment for natural selection on a set of biological types present in a population over a specified period of time. The second specifies an environment relevant to extinction of types in a population; this kind of environment is especially relevant to certain kinds of long-term evolution.     

Notes on selective influence, probabilistic causality, and probabilistic dimensionality

The paper provides conceptual clarifications for the issues related to the dependence of jointly distributed systems of random entities on external factors. This includes the theory of selective influence as proposed in Dzhafarov [(2003a). Selective influence through conditional independence. Psychometrika, 68, 7-26] and generalized versions of the notions of probabilistic causality [Suppes, P., & Zanotti, M. (1981). When are probabilistic explanations possible? Synthese, 48, 191-199] and dimensionality in the latent variable models [Levine, M. V. (2003). Dimension in latent variable models. Journal of Mathematical Psychology, 47, 450-466]. One of the basic observations is that any system of random entities whose joint distribution depends on a factor set can be represented by functions of two arguments: a single factor-independent source of randomness and the factor set itself. In the case of random variables (i.e., real-valued random entities endowed with Borel sigma-algebras) the single source of randomness can be chosen to be any random variable with a continuous distribution (e.g., uniformly distributed between 0 and 1).     

Estimating the population size of transgender women in San Francisco using multiple methods, 2013

Purpose: To estimate the number of adult transgender women (TGW) in San Francisco and to provide an example of how estimation can be conducted.

Methods: Using nine different services accessed by the TGW population, the service multiplier, integrated into a respondent-driven sampling (RDS) survey of TGW, was used to calculate nine estimates of the TGW population in San Francisco. Both the successive sampling method, also integrated into the RDS survey of TGW, and a population proportion from the literature each calculated an additional estimate of the TGW population. The median of all 11 estimates was calculated to present a single estimate of the TGW population in San Francisco.

Results: The median of estimates was 978 TGW in San Francisco (plausibility bounds 635 – 1,400). This estimate is consistent with known cases of HIV among TGW and surveys on the prevalence of infection in the TGW population.

Conclusion: Using multiple methods, we estimate the TGW population size to be 0.13% of the San Francisco population. Despite small numbers, TGW bear a disproportionate burden of HIV infection in San Francisco. TGW are a priority for HIV care and prevention services.     

Reducing cognitive biases in probabilistic reasoning by the use of logarithm formats

Research on probability judgment has traditionally emphasized that people are susceptible to biases because they rely on “variable substitution”: the assessment of normative variables is replaced by assessment of heuristic, subjective variables. A recent proposal is that many of these biases may rather derive from constraints on cognitive integration, where the capacity-limited and sequential nature of controlled judgment promotes linear additive integration, in contrast to many integration rules of probability theory (Juslin, Nilsson, & Winman, 2009). A key implication by this theory is that it should be possible to improve peoples’ probabilistic reasoning by changing probability problems into logarithm formats that require additive rather than multiplicative integration. Three experiments demonstrate that recasting tasks in a way that allows people to arrive at the answers by additive integration decreases cognitive biases, and while people can rapidly learn to produce the correct answers in an additive formats, they have great difficulty doing so with a multiplicative format.     

Understanding cumulative risk

This paper summarizes the theory of simple cumulative risks—for example, the risk of food poisoning from the consumption of a series of portions of tainted food. Problems concerning such risks are extraordinarily difficult for naïve individuals, and the paper explains the reasons for this difficulty. It describes how naïve individuals usually attempt to estimate cumulative risks, and it outlines a computer program that models these methods. This account predicts that estimates can be improved if problems of cumulative risk are framed so that individuals can focus on the appropriate subset of cases. The paper reports two experiments that corroborated this prediction. They also showed that whether problems are stated in terms of frequencies (80 out of 100 people got food poisoning) or in terms of percentages (80% of people got food poisoning) did not reliably affect accuracy.     

Competition during the processing of quantifier scope ambiguities: Evidence from eye movements during reading

We investigated the processing of sentences containing a quantifier scope ambiguity, such as Kelly showed a photo to each critic, which is ambiguous between the indefinite phrase (a photo) having one or many referents. Ambiguity resolution requires the computation of relative quantifier scope, with either a photo or each critic taking wide scope, thereby determining the number of referents. Using eye tracking, we established that multiple factors, including the grammatical function and surface linear order of quantified phrases, along with their lexical characteristics, interact during the processing of relative quantifier scope, with conflict between factors incurring a processing cost. We discuss the results in terms of theoretical accounts attributing sentence-processing difficulty to either reanalysis (e.g., Fodor, 1982) or competition between rival analyses (e.g., Kurtzman & MacDonald, 1993).     

Updating: A psychologically basic situation of probability revision

The Bayesian model has been used in psychology as the standard reference for the study of probability revision. In the first part of this paper we show that this traditional choice restricts the scope of the experimental investigation of revision to a stable universe. This is the case of a situation that, technically, is known as focusing. We argue that it is essential for a better understanding of human probability revision to consider another situation called updating (Katsuno & Mendelzon, 1992 Katsuno, A. and Mendelzon, A. 1992. “On the difference between updating a knowledge base and revising it”. In Belief revision, Edited by: Gärdenfors, P. 183–203. Cambridge, , UK: Cambridge University Press. [Crossref] , [Google Scholar]), in which the universe is evolving. In that case the structure of the universe has definitely been transformed and the revision message conveys information on the resulting universe. The second part of the paper presents four experiments based on the Monty Hall puzzle that aim to show that updating is a natural frame for individuals to revise their beliefs.     

How Much Older Do You Get When a Wrinkle Appears on Your Face? Modifying Age Estimates by Number of Wrinkles

ABSTRACT

The present study investigated the influence of wrinkles on facial age judgments. In Experiment 1, preadolescents, young adults, and middle-aged adults made categorical age judgments for male and female faces. The qualitative (type of wrinkle) and quantitative (density of wrinkles and depth of furrows) contributions of wrinkles were analyzed. Results indicated that the greater the number of wrinkles and the depth of furrows, the older a face was rated. The roles of the gender of the face and the age of the participants were discussed. In Experiment 2, participants performed relative age judgments by comparing pairs of faces. Results revealed that the number of wrinkles had more influence on the perceived facial age than the type of wrinkle. A MDS analysis showed the main dimensions on which participants based their judgments, namely, the number of wrinkles and the depth of furrows. We conclude that the quantitative component is more likely to increase perceived facial age. Nevertheless, other variables, such as the gender of the face and the age of the participants, also seem to be involved in the age estimation process.