Women’s mobility and ‘transport-related social exclusion’ in Bishkek

This paper analyses gendered mobilities in Bishkek in the space of the most popular form of public transport: the minibus, or ‘marshrutka’. As the means by which women often access various important sites of daily life, the marshrutka itself is a site of negotiation and interaction. Utilizing theories of mobility and empirical data, we argue that marshrutkas are spaces that can give rise to two dichotomous conditions: positive marshrutka experiences may increase the social mobility of female passengers and subsequently increase social empowerment and influence, while negative ones can provide the grounds for social exclusion and gender inequality.     

Cyclical Evolution of the Global Right

An understanding of the current right‐wing national and transnational social movements can benefit from comparing them to the global and national conditions operating during their last appearance in the first half of the twentieth century and by carefully comparing twentieth‐century fascism with the neofascist and right‐wing populist movements that have been emerging in the twenty‐first century. This allows us to assess the similarities and differences, and to gain insights about what could be the consequences of the reemergence of populist nationalism and fascist movements. Our study uses the comparative evolutionary world‐systems perspective to study the Global Right from 1800 to the present. We see fascism as a form of capitalism that emerges when the capitalist project is in crisis. World historical waves of right‐wing populism and fascism are caused by the cycles of globalization and deglobalization, the rise and fall of hegemonic core powers, long business cycles (the Kondratieff wave), and interactions with both Centrist Liberalism and the Global Left. We consider how crises of the global capitalist system have produced right‐wing backlashes in the past, and how a future terminal crisis of capitalism could lead to a reemergence of a new form of authoritarian global governance or a reorganized global democracy in the future.     

CORRUPTION: TOP DOWN OR BOTTOM UP?

This article studies the impact of corruption on an economy with a hierarchical government. In particular, we study whether centralizing corruption within the higher level of government increases or decreases the total amount of corruption. We show that when the after-tax relative profitability of the formal sector as compared to that of the informal sector is high enough, adding a layer of government increases the total amount of corruption. By contrast, for high-enough public wages and/or an efficient monitoring technology of the bureaucratic system, centralization of corruption at the top of the government hierarchy redistributes bribe income from the lower level to the upper level. In the process, total corruption is reduced and the formal sector of the economy expands.     

Lives in limbo: Temporary Protected Status and immigrant identities

The United States formulates much of its immigration and refugee policy to match economic and political circumstances. We interpret these policy shifts as a set of graduated positions on immigration and refugee flows that attempts to discipline the lives of newcomers and, in so doing, shapes immigrant identities. In this article, we analyse the interplay between the US government and Salvadoran asylum applicants negotiating procedures that grant only temporary relief from deportation via the policy of Temporary Protected Status (TPS). We find that each policy shift results in the strategic renegotiation of asylum applicants’ identities so as to achieve the best opportunity for a successful outcome. Based on Foucault’s ideas of governmentality and Ong’s concept of flexible citizenship, we argue that what appears more superficially as a patchwork strategy of immigration laws and asylum practices may be theorized more deeply as a set of flexible responses by the state that turn on identity construction at different scales, and that aim to mediate transnational relations.     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

A study of simulated annealing and a revised cascade algorithm for image reconstruction

We describe an image reconstruction problem and the computational difficulties arising in determining the maximum a posteriori (MAP) estimate. Two algorithms for tackling the problem, iterated conditional modes (ICM) and simulated annealing, are usually applied pixel by pixel. The performance of this strategy can be poor, particularly for heavily degraded images, and as a potential improvement Jubb and Jennison (1991) suggest the cascade algorithm in which ICM is initially applied to coarser images formed by blocking squares of pixels. In this paper we attempt to resolve certain criticisms of cascade and present a version of the algorithm extended in definition and implementation. As an illustration we apply our new method to a synthetic aperture radar (SAR) image. We also carry out a study of simulated annealing, with and without cascade, applied to a more tractable minimization problem from which we gain insight into the properties of cascade algorithms.     

CALGARY FAMILY INTERVENTION MODEL: ONE WAY TO THINK ABOUT CHANGE

This article defines and describes the Calgary Family Intervention Model (CFIM). CFIM is an organizing framework conceptualizing the intersect between a particular domain (i.e., cognitive, affective, or behavioral) of family functioning and a specific intervention offered by a health professional. Examples and discussion of interventions such as storying the illness experience, encouraging respite, and asking interventive questions are presented. CFIM is one way that health professionals can conceptualize about change.     

Creating offshore-ready it professionals: A global perspective and strong collaborative skills are needed

Outsourcing of IT functions has become a widespread corporate practice, which has naturally led to concerns among IT works about how this affects their jobs. The issue is complex, and many companies are bringing their IT functions back inhouse. In light of this complexity, what skills do IT workers need to be com-petitive? We address this question first by reviewing the literature and then by examining two corporate case studies that have dealt with outsourcing issues. Based on this view of outsourcing, we discuss the skills that can provide a com-petitive advantage in the current environment.