Two models of unawareness: comparing the object-based and the subjective-state-space approaches

This article attempts to motivate a new approach to anti-realism (or nominalism) in the philosophy of mathematics. I will explore the strongest challenges to anti-realism, based on sympathetic interpretations of our intuitions that appear to support realism. I will argue that the current anti-realistic philosophies have not yet met these challenges, and that is why they cannot convince realists. Then, I will introduce a research project for a new, truly naturalistic, and completely scientific approach to philosophy of mathematics. It belongs to anti-realism, but can meet those challenges and can perhaps convince some realists, at least those who are also naturalists.     

Comparison of classical and modern methods for measuring and correcting for acquiescence

Likert-type self-report scales are frequently used in large-scale educational assessment of social-emotional skills. Self-report scales rely on the assumption that their items elicit information only about the trait they are supposed to measure. However, different response biases may threaten this assumption. Specifically, in children, the response style of acquiescence is an important source of systematic error. Balanced scales, including an equal number of positively and negatively keyed items, have been proposed as a solution to control for acquiescence, but the reasons why this design feature worked from the perspective of modern psychometric models have been underexplored. Three methods for controlling for acquiescence are compared: classical method by partialling out the mean; an item response theory method to measure differential person functioning (DPF); and multidimensional item response theory (MIRT) with random intercept. Comparative analyses are conducted on simulated ratings and on self-ratings provided by 40,649 students (aged 11–18) on a fully balanced 30-item scale assessing conscientious self-management. Acquiescence bias was explained as DPF and it was demonstrated that: the acquiescence index is highly related to DPF; balanced scales produce scores controlled for DPF; and MIRT factor scores are highly related to scores controlled for DPF and the random intercept is highly related to DPF.     

Real-life outgroup exposure,self-reported outgroup contact and the other-race effect

People are better at recognizing faces from their own racial or ethnic group compared with faces from other racial or ethnic groups, known as the other-‘race’ effect (ORE). Several theories of the ORE assume that memory for other-race faces is impaired because people have less contact with members of other racial or ethnic groups, resulting in lower visual expertise. The present research investigates contact theories of the ORE, using self-report contact measures and objective measures of potential outgroup exposure (estimated from participants' residential location and from GPS tracking). Across six studies (total N = 2660), we observed that White American and White German participants displayed better memory for White faces compared with Black or Middle Eastern faces, whereas Black American participants displayed similarly equal or better memory for White compared with Black faces. We did not observe any relations between the ORE and objective measures of potential outgroup exposure. Only in Studies 2a and 2b, we observed very small correlations (rs = −.08 to .06) between 4 out of 30 contact measures and the ORE. We discuss methodological limitations and implications for theories of the ORE.     

Triple Bottomline Many‐Objective‐Based Decision Making for a Land Use Management Problem

A land use many‐objective optimization problem for a 1500‐ha farm with 315 paddocks was formulated with 14 objectives (maximizing sawlog production, pulpwood production, milksolids, beef, sheep meat, wool, carbon sequestration, water production, income and Earnings Before Interest and Tax; and minimizing costs, nitrate leaching, phosphorus loss and sedimentation). This was solved using a modified Reference‐point‐based Non‐dominated Sorting Genetic Algorithm II augmented by simulated epigenetic operations. The search space had complex variable interactions and was based on economic data and several interoperating simulation models. The solution was an approximation of a Hyperspace Pareto Frontier (HPF), where each non‐dominated trade‐off point represented a set of land‐use management actions taken within a 10‐year period and their related management options, spanning a planning period of 50 years. A trade‐off analysis was achieved using Hyper‐Radial Visualization (HRV) by collapsing the HPF into a 2‐D visualization capability through an interactive virtual reality (VR)‐based method, thereby facilitating intuitive selection of a sound compromise solution dictated by the decision makers' preferences under uncertainty conditions. Four scenarios of the HRV were considered emphasizing economic, sedimentation and nitrate leaching aspects—giving rise to a triple bottomline (i.e. the economic, environmental and social complex, where the social aspect is represented by the preferences of the various stakeholders). Highlights of the proposed approach are the development of an innovative epigenetics‐based multi‐objective optimizer, uncertainty incorporation in the search space data and decision making on a multi‐dimensional space through a VR‐simulation‐based visual steering process controlled at its core by a multi‐criterion decision making‐based process. This approach has widespread applicability to many other ‘wicked’ societal problem‐solving tasks. Copyright © 2014 John Wiley & Sons, Ltd.