Preference purification and the inner rational agent:A critique of the conventional wisdom of behavioural welfare economics

Neoclassical economics assumes that individuals have stable and context-independent preferences, and uses preference-satisfaction as a normative criterion. By calling this assumption into question, behavioural findings cause fundamental problems for normative economics. A common response to these problems is to treat deviations from conventional rational-choice theory as mistakes, and to try to reconstruct the preferences that individuals would have acted on, had they reasoned correctly. We argue that this preference purification approach implicitly uses a dualistic model of the human being, in which an inner rational agent is trapped in an outer psychological shell. This model is psychologically and philosophically problematic

Thurstonian Scaling of Compositional Questionnaire Data

To prevent response biases, personality questionnaires may use comparative response formats. These include forced choice, where respondents choose among a number of items, and quantitative comparisons, where respondents indicate the extent to which items are preferred to each other. The present article extends Thurstonian modeling of binary choice data (Brown & Maydeu-Olivares, 2011a) to “proportion-of-total” (compositional) formats. Following Aitchison (1982), compositional item data are transformed into log-ratios, conceptualized as differences of latent item utilities. The mean and covariance structure of the log-ratios is modelled using Confirmatory Factor Analysis (CFA), where the item utilities are first-order factors, and personal attributes measured by a questionnaire are second-order factors. A simulation study with two sample sizes, N=300 and N=1000, shows that the method provides very good recovery of true parameters and near-nominal rejection rates. The approach is illustrated with empirical data from N=317 students, comparing model parameters obtained with compositional and Likert scale versions of a Big Five measure. The results show that the proposed model successfully captures the latent structures and person scores on the measured traits

Phase control and measurement in digital microscopy

The ongoing merger of the digital and optical components of the modern microscope is creating opportunities for new measurement techniques, along with new challenges for optical modelling. This thesis investigates several such opportunities and challenges which are particularly relevant to biomedical imaging. Fourier optics is used throughout the thesis as the underlying conceptual model, with a particular emphasis on three--dimensional Fourier optics. A new challenge for optical modelling provided by digital microscopy is the relaxation of traditional symmetry constraints on optical design. An extension of optical transfer function theory to deal with arbitrary lens pupil functions is presented in this thesis. This is used to chart the 3D vectorial structure of the spatial frequency spectrum of the intensity in the focal region of a high aperture lens when illuminated by linearly polarised beam. Wavefront coding has been used successfully in paraxial imaging systems to extend the depth of field. This is achieved by controlling the pupil phase with a cubic phase mask, and thereby balancing optical behaviour with digital processing. In this thesis I present a high aperture vectorial model for focusing with a cubic phase mask, and compare it with results calculated using the paraxial approximation. The effect of a refractive index change is also explored. High aperture measurements of the point spread function are reported, along with experimental confirmation of high aperture extended depth of field imaging of a biological specimen. Differential interference contrast is a popular method for imaging phase changes in otherwise transparent biological specimens. In this thesis I report on a new isotropic algorithm for retrieving the phase from differential interference contrast images of the phase gradient, using phase shifting, two directions of shear, and non--iterative Fourier phase integration incorporating a modified spiral phase transform. This method does not assume that the specimen has a constant amplitude. A simulation is presented which demonstrates good agreement between the retrieved phase and the phase of the simulated object, with excellent immunity to imaging noise

Explaining Evidence Denial as Motivated Pragmatically Rational Epistemic Irrationality

This paper introduces a model for evidence denial that explains this behavior as a manifestation of rationality and it is based on the contention that social values (measurable as utilities) often underwrite these sorts of responses. Moreover, it is contended that the value associated with group membership in particular can override epistemic reason when the expected utility of a belief or belief system is great. However, it is also true that it appears to be the case that it is still possible for such unreasonable believers to reverse this sort of dogmatism and to change their beliefs in a way that is epistemically rational. The conjecture made here is that we should expect this to happen only when the expected utility of the beliefs in question dips below a threshold where the utility value of continued dogmatism and the associated group membership is no longer sufficient to motivate defusing the counter-evidence that tells against such epistemically irrational beliefs

The use of happiness research for public policy

Research on happiness tends to follow a "benevolent dictator" approach where politicians pursue people's happiness. This paper takes an antithetic approach based on the insights of public choice theory. First, we inquire how the results of happiness research may be used to improve the choice of institutions. Second, we show that the policy approach matters for the choice of research questions and the kind of knowledge happiness research aims to provide. Third, we emphasize that there is no shortcut to an optimal policy maximizing some happiness indicator or social welfare function since governments have an incentive to manipulate this indicator

Analytical reasoning task reveals limits of social learning in networks

Social learning -by observing and copying others- is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is our ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of lab-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions, and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias,' which limits their social learning to the output, rather than the process, of their peers' reasoning -even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behavior through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning

Honesty Requires Time (and Lack of Justifications)

Recent research suggests that refraining from cheating in tempting situations requires self-control, which indicates that serving self-interest is an automatic tendency. However, evidence also suggests that people cheat to the extent that they can justify their unethical behavior to themselves. To merge these different lines of research, we adopted a dual-system approach that distinguished between the intuitive and deliberative cognitive systems. We suggest that for people to restrict their dishonest behavior, they need to have enough time and no justifications for self-serving unethical behavior. We employed an anonymous die-under-cup task in which participants privately rolled a die and reported the outcome to determine their pay. We manipulated the time available for participants to report their outcome (short vs. ample). The results of two experiments support our prediction, revealing that the dark side of people’s automatic self-serving tendency may be overcome when time to decide is ample and private justifications for dishonesty are not available

Blaming Bill Gates AGAIN! Misuse, overuse and misunderstanding of performance data in sport

Recently in Sport, Education and Society, Williams and Manley (2014) argued against the heavy reliance on technology in professional Rugby Union and elite sport in general. In summary, technology is presented as an elitist, ‘gold standard’ villain that management and coaches use to exert control and by which players lose autonomy, identity, motivation, social interactions and expertise. In this article we suggest that the sociological interpretations and implications offered by Williams and Manley may be somewhat limited when viewed in isolation. In doing so, we identify some core methodological issues in Williams and Manley’s study and critically consider important arguments for utilising technology; notably, to inform coach decision making and generate player empowerment. Secondly, we present a different, yet perhaps equally concerning, practice-oriented interpretation of the same results but from alternative coaching and expertise literature. Accordingly, we suggest that Williams and Manley have perhaps raised their alarm prematurely, inappropriately and on somewhat shaky foundations. We also hope to stimulate others to consider contrary positions, or at least to think about this topic in greater detail. More specifically, we encourage coaches and academics to think carefully about what technology is employed, how and why, and then the means by which these decisions are discussed with and, preferably, sold to players. Certainly, technology can significantly enhance coach decision making and practice, while also helping players to optimise their focus, empowerment and independence in knowing how to achieve their personal and collective goals

Nudging art lovers to donate.

Many nonprofit organizations face revenue uncertainty due to funding cuts. It is crucial for them to supplement existing revenue streams by private donations, and apply thoughtful market segmentation in their pursuit of donors. We introduce the behavioral concept of ‘nudge’ based on the possibility of loss aversion affecting willingness-to-donate, and investigate its implications for fundraising strategies. Potential donors are nudged to donate by the hypothetical scenario of ‘losing’ an existing exhibition, and also by that of ‘gaining’ an additional exhibition. We observe significant loss aversion effects as frequent gallery-goers donate more in order to avoid losing an exhibition. While both prospective gain and loss scenarios are effective in nudging non-frequent gallery-goers, the prospect of enjoying ‘one more’ event is observed to be stronger. We argue that there may be scope to increase support for nonprofit organizations, particularly in the cultural sector, by exploiting the psychological characteristics of prospective donors

The diplomat's dilemma: Maximal power for minimal effort in social networks

Closeness is a global measure of centrality in networks, and a proxy for how influential actors are in social networks. In most network models, and many empirical networks, closeness is strongly correlated with degree. However, in social networks there is a cost of maintaining social ties. This leads to a situation (that can occur in the professional social networks of executives, lobbyists, diplomats and so on) where agents have the conflicting objectives of aiming for centrality while simultaneously keeping the degree low. We investigate this situation in an adaptive network-evolution model where agents optimize their positions in the network following individual strategies, and using only local information. The strategies are also optimized, based on the success of the agent and its neighbors. We measure and describe the time evolution of the network and the agents' strategies.Comment: Submitted to Adaptive Networks: Theory, Models and Applications, to be published from Springe