The baby effect and young male syndrome : social influences on cooperative risk-taking in women and men

Parental investment theory predicts differences in risk-taking for females and males as a consequence of reproductive context, with females attempting to reduce risks in relation to their own offspring (here called the baby effect) and males taking more risks in competition with one another (young male syndrome). The experiment we report tests these predictions in a cooperative context by introducing the Social Balloon Analogue Risk Task—the Balloon Analogue Risk Task modified to include a social partner (adult male, adult female, or baby)—along with a commitment device in which participants choose among several possible social partners, with whom they will share their earnings. Results were consistent with the predictions of parental investment theory. Females did not change their levels of risk-taking when paired with adult males or females, but showed a strong reduction in risk when paired with babies. Consistent with previous research, males were strongly inclined to take more risks when paired with another male of the same age, but males showed no change in risk-taking when paired with a female of the same age or a child. The current work provides the first experimental evidence of gender differences in cooperative social risk-taking, as well as the first experimental evidence of a mediator of female risk-taking, i.e., babies

The emotional recall task : juxtaposing recall and recognition-based affect scales

Existing affect scales typically involve recognition of emotions from a predetermined emotion checklist. However, a recognition-based checklist may fail to capture sufficient breadth and specificity of an individual’s recalled emotional experiences and may therefore miss emotions that frequently come to mind. More generally, how do recalled emotions differ from recognized emotions? To address these issues, we present and evaluate an affect scale based on recalled emotions. Participants are asked to produce 10 words that best described their emotions over the past month and then to rate each emotion for how often it was experienced. We show that average weighted valence of the words produced in this task, the Emotional Recall Task (ERT), is strongly correlated with scales related to general affect, such as the PANAS, Ryff’s Scales of Psychological Well-being, the Satisfaction with Life Scale, Depression Anxiety and Stress Scales, and a few other related scales. We further show that the Emotional Recall Task captures a breadth and specificity of emotions not available in other scales but that are nonetheless commonly reported as experienced emotions. We test a general version of the ERT (the ERT general) that is language neutral and can be used across cultures. Finally, we show that the ERT is valid in a test-retest paradigm. In sum, the ERT measures affect based on emotion terms relevant to an individual’s idiosyncratic experience. It is consistent with recognition-based scales, but also offers a new direction towards enriching our understanding of individual differences in recalled and recognized emotions

The UK recession in context — what do three centuries of data tell us?

The Quarterly Bulletin has a long tradition of using historical data to help analyse the latest developments in the UK economy. To mark the Bulletin’s 50th anniversary, this article places the recent UK recession in a long-run historical context. It draws on the extensive literature on UK economic history and analyses a wide range of macroeconomic and financial data going back to the 18th century. The UK economy has undergone major structural change over this period but such historical comparisons can provide lessons for the current economic situation.

The dark side of information proliferation

There are well-understood psychological limits on our capacity to process information. As information proliferation—the consumption and sharing of information—increases through social media and other communications technology, these limits create an attentional bottleneck, favoring information that is more likely to be searched for, attended to, comprehended, encoded, and later reproduced. In information-rich environments, this bottleneck influences the evolution of information via four forces of cognitive selection, selecting for information that is beliefconsistent, negative, social, and predictive. Selection for belief-consistent information leads balanced information to support increasingly polarized views. Selection for negative information amplifies information about downside risks and crowds out potential benefits. Selection for social information drives herding, impairs objective assessments, and reduces exploration for solutions to hard problems. Selection for predictive patterns drives overfitting, the replication crisis, and risk seeking. This article summarizes the negative implications of these forces of cognitive selection and presents eight warnings, which represent severe pitfalls for the naive informavore, accelerating extremism, hysteria, herding, and the proliferation of misinformation

The Recent Rise of Southern Banking

Between 1984 and 1986 the legislatures of several southern states enacted changes to their banking laws that enabled banking companies in Southern Region states to acquire and be acquired by banking companies in other Southern Region states, as long as these companies qualified as “Southern.” The purpose of the compact was to allow some southern banking companies an opportunity to grow and gain financial strength before full interstate banking was permitted. This study shows that the compact was successful. In 1985 no southern banking companies were among the top ten banks in the country, but by 2005 four were. Furthermore, no major southern bank has been acquired by a U.S. banking company outside of the South, although several southern banking companies have bought banks in other regions. The southern economy and its banking industry have benefited, although the benefits have been unevenly spread among states

Humor norms for 4,997 English words

Humor ratings are provided for 4,997 English words collected from 821 participants using an online crowd-sourcing platform. Each participant rated 211 words on a scale from 1 (humorless) to 5 (humorous). To provide for comparisons across norms, words were chosen from a set common to a number of previously collected norms (e.g., arousal, valence, dominance, concreteness, age of acquisition, and reaction time). The complete dataset provides researchers with a list of humor ratings and includes information on gender, age, and educational differences. Results of analyses show that the ratings have reliability on a par with previous ratings and are not well predicted by existing norms

Description-experience gap in choice deferral

Facing a large set of alternatives has previously been reported to lead to choice overload, including choice deferral. Recent studies, however, imply that choice deferral is more tightly associated with the difficulty in evaluating alternatives than with set size: when alternatives are difficult to evaluate, people often defer a choice. This implication is examined in the present study, using alternatives with probabilistic payoffs in 2 paradigms: the description paradigm—with full probability and payoff information provided at 1 time—and the sampling paradigm—with search revealing 1 payoff at a time and repeated search required to derive probabilities and payoffs. The results show that in both paradigms, choice deferral is less frequent when set size is large. Also, the difficulty in evaluating alternatives influences choice deferral in the description paradigm but not in the sampling paradigm: when a payoff from an alternative can take many possible values, a choice is more likely deferred in the description paradigm. In the sampling paradigm, in contrast, information search is often insufficient for people to recognize the difficulty in evaluating alternatives. These results point to a description-experience gap in choice deferral

Bias in Zipf's Law Estimators

The prevailing maximum likelihood estimators for inferring power law models from rank-frequency data are biased. The source of this bias is an inappropriate likelihood function. The correct likelihood function is derived and shown to be computationally intractable. A more computationally efficient method of approximate Bayesian computation (ABC) is explored. This method is shown to have less bias for data generated from idealised rank-frequency Zipfian distributions. However, the existing estimators and the ABC estimator described here assume that words are drawn from a simple probability distribution, while language is a much more complex process. We show that this false assumption leads to continued biases when applying any of these methods to natural language to estimate Zipf exponents. We recommend that researchers be aware of these biases when investigating power laws in rank-frequency data.Comment: 15 pages, 11 figure