We tested a social-identity relative deprivation (SIRD) model predicting Scottish nationalist beliefs and intention to vote for the separatist Scottish Nationalist Party (SNP). Data were from a survey of a large and representative sample of Scottish teenagers administered in the late 1980s. The SIRD model distinguishes effects of group-based and personal relative deprivation, which should be independent of one another. Importantly, social change beliefs should mediate the effects of both collective relative deprivation and group identification on protest intentions (in this case intention to vote for the SNP). Egoistic relative deprivation should be the strongest predictor of feelings of depression. Using structural equation modelling, the results strongly support this model and replicate in two different cohorts.How do social identity and relative deprivation affect support for social change and personal well-being? This broad question has substantial relevance to any country facing a general election, as well as less-formalized changes in which collectives mobilize to challenge the prevailing political structure. In many instances, there are political parties whose aim is to gain independent governance or sovereignty for a particular disadvantaged region within a country. Individuals in such regions typically face both personal and collective deprivation, so the question of whether they become personally distressed and demoralized or become motivated to achieve social change by supporting separatist movements is of fundamental importance. This article proposes a social identity-relative deprivation (SIRD) model that distinguishes the impact of collective deprivation from personal deprivation, and specifies a route through which social identity and collective relative deprivation (CRD) promote a social change belief structure. This structure, in turn, mobilizes support for separatist political movements,

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Current motion-drive algorithms have a number of coef cients that are selected to tune the motion of the simulator. Little attention has been given to the process of selecting the most appropriate coef cient values. Final tuning is best accomplished using experienced evaluation pilots to provide feedback to a washout lter expert who adjusts the coef cients in an attempt to satisfy the pilot. This paper presents the development of a tuning paradigm and the capturing of such within an expert system. The focus of this development is the University of Toronto classical algorithm, but the results are relevant to alternative classical and similarly structured adaptive algorithms. This paper provides the groundwork required to develop the tuning paradigm. The necessity of this subjective tuning process is defended. Motion cueing error sources within the classical algorithm are revealed, and coef cient adjustments that reduce the errors are presented. Nomenclaturea = acceleration a2, f 1, bSH, bH = intermediate washout variables F A = aircraft body-axis frame F I = inertial frame F P = body frame attached to center of pilot's head F S = simulator body-axis frame f = speci c force gY = gravity vector expressed in F Y k 2 = lter gain LIS = rotation matrix that transforms vector components from F S to F I S = simulator displacement s = Laplace operator TS = transformation from angular velocity to Euler angle rates b S = simulator Euler angles [f S , u S , c S ] T vb 2 = rst-order high-pass break frequency v , z hp hp 2 2 = second-order high-pass break frequency and damping ratio v , z lp lp 2 2 = second-order low-pass break frequency and damping ratio v XY = angular rate of F X expressed in F Y Subscript XY = property of F X expressed in F Y Superscripts x = component of quantity ( ) = Laplace transform of ( )

Currently in Canada, there is a widespread underemployment among foreign-trained immigrants. This is because potential employers often have to evaluate unfamiliar foreign qualifications that, regrettably, are often misunderstood and undervalued. This questionnaire study tested a model that integrates relative deprivation theory with social identity theory to predict the degree to which skilled migrants from Asia and Africa with credentialing problems protest this systemic discriminatory barrier (N=180). In the model, the strength of cultural and national identifications are conceptualized as opposing motivational forces that, along with collective relative deprivation (CRD), directly impact protest intentions. As well, the model specifies that the so-called 'affective' component of CRD consists of an attribution of blame (perceived discrimination) and associated emotions. Structural equation modelling shows that the model is a good fit to the data. As hypothesized, significant path coefficients show that the strength of cultural identity increases and the strength of Canadian identity decreases the degree to which the respondents feel that immigrants suffer discrimination which, in-turn, influenced their intentions to take protest actions. The implications of these findings for the integration of relative deprivation and social identity theories are discussed.

The effects of eight in-vehicle tasks on driver distraction were measured in a large, moving-base driving simulator. Forty-eight adults, ranging in age from 35 to 66, and 15 teenagers participated in the simulated drive. Hand-held and hands-free versions of phone dialing, voicemail retrieval, and incoming calls represented six of the eight tasks. Manual radio tuning and climate control adjustment were also included to allow comparison with tasks that have traditionally been present in vehicles. During the drive the participants were asked to respond to sudden movements in surrounding traffic. The driver’s ability to detect these sudden movements or events changed with the nature of the in-vehicle tasks that were being performed. Driving performance measures such as lane violations and heading error were also computed. The performance of the adult group was compared with the performance of the teenage drivers. Compared with the adults, the teens were found to choose unsafe following distances, have poor vehicle control skills, and be more prone to distraction from hand-held phone tasks.