Extremizing and Antiextremizing in Bayesian Ensembles of Binary-Event Forecasts

Many organizations combine forecasts of probabilities of binary events to support critical business decisions, such as the approval of credit or the recommendation of a drug. To aggregate individual probabilities, we offer a new method based on Bayesian principles that can help identify why and when combined probabilities need to be extremized. Extremizing is typically viewed as shifting the average probability farther from one half; we emphasize that it is more suitable to define extremizing as shifting it farther from the base rate. We introduce the notion of antiextremizing, cases in which it might be beneficial to make average probabilities less extreme. Analytically, we find that our Bayesian ensembles often extremize the average forecast but sometimes antiextremize instead. On several publicly available data sets, we demonstrate that our Bayesian ensemble performs well and antiextremizes anywhere from 18% to 73% of the cases. Antiextremizing is required more often when there is bracketing with respect to the base rate among the probabilities being aggregated than with no bracketing.

Higher-order learning

We design a novel experiment to study how subjects update their beliefs about the beliefs of others. Three players receive sequential signals about an unknown state of the world. Player 1 reports her beliefs about the state; Player 2 simultaneously reports her beliefs about the beliefs of Player 1; Player 3 simultaneously reports her beliefs about the beliefs of Player 2. We say that beliefs exhibit higher-order learning if the beliefs of Player k about the beliefs of Player $$k-1$$ k - 1 become more accurate as more signals are observed. We find that some of the predicted dynamics of higher-order beliefs are reflected in the data; in particular, higher-order beliefs are updated more slowly with private than public information. However, higher-order learning fails even after a large number of signals is observed. We argue that this result is driven by base-rate neglect, heterogeneity in updating processes, and subjects’ failure to correctly take learning rules of others into account.

Is Automation of Statistical Reasoning a Suitable Mindware in a Base-Rate Neglect Task?

Until recently, studies within the dual-process approach were mainly focused on group differences in processing, and individual differences were neglected. However, individual differences have proven to be a significant factor in conflict detection efficiency and the overall success in base-rate neglect and similar tasks. This should be taken into consideration within the framework of the Hybrid Model of Dual Processing. New tendencies in the development of this model have focused attention on the degree of mindware instantiation as a predictor of base-rate neglect task efficiency. This study aimed to examine the relationship between mindware and base-rate neglect task efficiency and to test and explore the relationship between base-rate response frequency and conflict detection efficiency and the degree of mindware instantiation. All participants solved base-rate neglect tasks, made judgments of confidence in their responses, and solved the Statistical Reasoning Test, Cognitive Reflection Test and Numeracy Scale. We used the Statistical Reasoning Test as a measure of mindware instantiation. The degree of mindware instantiation was found to be the only significant predictor of base-rate neglect task efficiency and the results showed that participants with a higher degree of mindware instantiation generally made more base-rate responses. No correlation was found between the degree of mindware instantiation and conflict detection efficiency. These findings support the hypothesis that the power of logical intuition depends on the individual’s degree of mindware instantiation. Therefore, the results of this research indicate the importance of further research into the role of statistical reasoning in base-rate neglect task efficiency. However, we discuss that there are some methodological limitations in this research which might explain why the degree of mindware instantiation had no relationship with conflict efficiency.

Top Ten Behavioral Biases in Project Management: An Overview

Behavioral science has witnessed an explosion in the number of biases identified by behavioral scientists, to more than 200 at present. This article identifies the 10 most important behavioral biases for project management. First, we argue it is a mistake to equate behavioral bias with cognitive bias, as is common. Cognitive bias is half the story; political bias the other half. Second, we list the top 10 behavioral biases in project management: (1) strategic misrepresentation, (2) optimism bias, (3) uniqueness bias, (4) the planning fallacy, (5) overconfidence bias, (6) hindsight bias, (7) availability bias, (8) the base rate fallacy, (9) anchoring, and (10) escalation of commitment. Each bias is defined, and its impacts on project management are explained, with examples. Third, base rate neglect is identified as a primary reason that projects underperform. This is supported by presentation of the most comprehensive set of base rates that exist in project management scholarship, from 2,062 projects. Finally, recent findings of power law outcomes in project performance are identified as a possible first stage in discovering a general theory of project management, with more fundamental and more scientific explanations of project outcomes than found in conventional theory.

Dimensional Latent Structure of Callous-Unemotional Traits in German Adolescents: Results from Taxometric Analyses

A large amount of research has addressed the issue of the latent status of psychiatric disorders and related phenomena. We used a new taxometric approach developed by Ruscio to examine the latent status of callous-unemotional (CU) traits in a large representative study of German ninth graders (N = 3,878). Rather than estimating a putative taxon base rate and using that estimate to generate the taxon comparative data, we estimated CCFI profiles with each base rate estimate between 2.5% and 97.5% in increments of 2.5%. Results of different indicator sets clearly suggested a dimensional solution. This finding is consistent with different studies showing the dimensionality of psychopathy in adolescents. In summary, the results of this study point to the need for critical reflection in defining a high-risk-group in the context of CU traits. However, further studies are necessary to substantiate this result in different samples using different measurement approaches.

Consumer culture, precarious incomes and mass indebtedness: Borrowing from uncertain futures, consuming in precarious times

In recent years, labour markets have been characterised by stagnant wages, reduced incomes and growing insecurity supplemented by the ongoing proliferation of outstanding payment obligations at almost all levels of economy and society. We draw upon current debates in social and economic theory to explore the disconnect between the deterioration of late capitalism’s distributive measures and the relative vitality of consumer cultures, suggesting that the latter relies substantially on immaterial, credit-based payment means to bridge the gap between the fundamental fantasy of ‘more and better’ and the decline of material productivity denoted by base rate of profit. We then use this disconnect as a breach-point for an in-depth interdisciplinary discussion of the substantive and ideological function of credit.