Repetition blindness: The survival of the grouped

The repetition blindness (RB) effect demonstrates that people often fail to detect the second presentation of an identical object (e.g., Kanwisher, 1987). Grouping of identical items is a well-documented perceptual phenomenon, and this grouping generally facilitates perception. These two effects pose a puzzle: RB impairs perception, while perceptual grouping improves it. Here, we combined these two effects and studied how they interact. In a series of three experiments, we presented repeated items in a simultaneous string, while manipulating the organization of the repeated items in groups within a string. We observed an interaction between RB and grouping that we summarize with a rule that we call “the survival of the grouped”: In essence, the ability to group repeated elements protects them from RB. These findings are discussed within the framework of the object file theory.     

Increasing organ donor registration rates by providing an immediate and complete registration opportunity: an experimental assessment of the IIFF model

The IIFF model of organ donation holds that the simultaneous presence of four factors directly influence donor registration: (1) immediate and complete registration opportunity (ICRO), (2) information, (3) focused engagement, and (4) favorable activation. Two field experiments examined the impact of an ICRO on organ donation registration. In Study 1, participants were at town halls where they knew organ donation was to be discussed. Registration cards were distributed and then collected at the end of the session in half of the town halls. For the other half, participants were asked to mail in completed cards. In three US cities, participants given an ICRO registered at a significantly greater rate (z?=?4.865, p?相似文献   

Propension à discriminer à l’égard du genre et dominance sociale

This work aims to study the propensity to discriminate (PTD) (Dovidio & Helb, 2005 ; Tisserant, Wagner & Barth, 2010) against gender and other salient criteria in the working place, such as ethnic origin and religious background. More precisely, we investigated the link between PTD and the social dominance orientation (Sidanius & Pratto, 1999). 119 counsellors from French employment services answered a questionnaire dealing on concepts and attitudes towards social groups. Results show that social dominance, as a system of belief justifying social inequalities, generally predict the PTD of individuals, whatever the criterion of discrimination considered. The sex of counsellors can be considered as a moderating variable since females are less likely to accept inequalities than males do. We discuss the need for work and organizational psychologists to invest, alongside the managers, this field of research on equality, non-discrimination and diversity (ENDD).     

Setting the bar: divergent sociocultural norms for women's and men's ideal appearance in real-world contexts

Research suggests that exposure to sociocultural norms for idealized appearance can reduce both women's and men's body satisfaction. Despite comparable effects for both genders in the lab, in the “real-world” women's body satisfaction is chronically lower than men's. Real-world gender differences may arise from discrepancies in men's and women's everyday exposure to norms. Across eight studies using a variety of content analysis, survey, and experimental methods, we examine differences in sociocultural norms for ideal appearance pertaining to women and men in “daily life” contexts. We demonstrate that appearance norms encountered by women in daily life are more rigid, homogenous and pervasive than those for men, and that more messages implying the attainability of the ideal appearance are directed at women. Finally, experimental results show that homogeneous, rigid norms (like those typically encountered by women) are more harmful to body image than heterogeneous, flexible norms (like those typically encountered by men).     

Mapping Uncertainties in the Upstream: The Case of PLGA Nanoparticles in Salmon Vaccines

The diversity of nanotechnologies and of the governance challenges that their applications raise calls for exploration and learning across different cases. We present an Upstream Oversight Assessment (UOA) of expected benefits and potential harms of nanoparticles made of a synthetic polymer (PLGA) to improve vaccines for farmed salmon. Suggested by Jennifer Kuzma and colleagues, an UOA may help identify and prioritise research needs, and it may support evaluations of the adequacy of relevant existing regulatory frameworks. In this work, the UOA approach is modified and supported with elements from the uncertainty analysis framework developed by Warren Walker and colleagues. Empirically, we draw on relevant available published literature and insights generated in an ongoing nanoparticle salmon vaccine project, in which one of the authors participates. Nanotechnologies have not previously been encountered in the regulatory context of fish vaccines, which in part raises unique challenges due to prospective large scale vaccine use in semi-open aquatic systems. Strengthened through cooperation between ELSA and technology researchers we found the UOA useful for an early mapping of benefits and concerns, and for identifying areas in need of further research prior to a nanoparticle based salmon vaccine is developed and taken into use. We consider our approach to represent one among several complementing initiatives that seek to contribute to early stage evaluations of possible negative side effects, broadly conceived, in order to facilitate a more robust nanotechnology development.     

Do complex models increase prediction of complex behaviours? Predicting driving ability in people with brain disorders

Prediction of complex behavioural tasks via relatively simple modelling techniques, such as logistic regression and discriminant analysis, often has limited success. We hypothesized that to more accurately model complex behaviour, more complex models, such as kernel-based methods, would be needed. To test this hypothesis, we assessed the value of six modelling approaches for predicting driving ability based on performance on computerized sensory-motor and cognitive tests (SMCTests?) in 501 people with brain disorders. The models included three models previously used to predict driving ability (discriminant analysis, DA; binary logistic regression, BLR; and nonlinear causal resource analysis, NCRA) and three kernel methods (support vector machine, SVM; product kernel density, PK; and kernel product density, KP). At the classification level, two kernel methods were substantially more accurate at classifying on-road pass or fail (SVM 99.6%, PK 99.8%) than the other models (DA 76%, BLR 78%, NCRA 74%, KP 81%). However, accuracy decreased substantially for all of the kernel models when cross-validation techniques were used to estimate prediction of on-road pass or fail in an independent referral group (SVM 73-76%, PK 72-73%, KP 71-72%) but decreased only slightly for DA (74-75%) and BLR (75-76%). Cross-validation of NCRA was not possible. In conclusion, while kernel-based models are successful at modelling complex data at a classification level, this is likely to be due to overfitting of the data, which does not lead to an improvement in accuracy in independent data over and above the accuracy of other less complex modelling techniques.