53 resultados para Police corruption


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Two field studies demonstrated that majority and minority size moderate perceived group variability. In Study 1 we found an outgroup homogeneity (OH) effect for female nurses in the majority, but an ingroup homogeneity (IH) effect for a token minority of male nurses. In Study 2 we found similar effects in a different setting - an OH effect for policemen in the majority and an IH effect for policewomen in the minority. Although measures of visibility, status, and, especially, familiarity tended to show the same pattern as perceived variability, there was no evidence that they mediated perceived dispersion. Results are discussed in terms of group size, rather than gender, being moderators of perceived variability, and with reference to Kanter's (1977a, 1977b) theory of group proportions.

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Would multinational corporation (MNC) subsidiaries be more profitable in host countries where corruption is less severe? Would MNC subsidiaries be more profitable in less corrupt countries if they focus on local sales? This paper examines the impact of the level of corruption on the profitability of US MNCs in the Asia Pacific region. Using foreign direct investment (FDI) data archived by the US Bureau of Economic Analysis and corruption data reported by the World Bank, we find that MNC subsidiaries located in countries with a lower level of corruption are more profitable. In addition, MNC subsidiaries with a greater focus on local sales are more profitable when the corruption level is low. This study contributes to the literature by showing that when local sales are important to MNC subsidiaries, a lower level of corruption by host countries positively affects the profitability of the MNC subsidiaries.

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This paper studies the representation of suburbs as a place of anguish in the “Special Police” novels (Fleuve Noir publisher, Paris) by Frédéric Dard. This anxiety, it is argued, is what lends this collection of 25 novels some of their essential qualities, their unhealthy climate and absolute darkness. Dard’s suburbs fit into the traditions of realism; but the atmosphere, characters and plots owe to the American hardboiled school and like in film noir, space is stylized and dramatized, and often used to express a judgment of moral nature. Spatial representations in these novels are part of a critique of civilization and constitute a comment on the social modernization and public intervention in the development of the French territory in the postwar period. The novels written by Frédéric Dard from the mid-1950s to mid-1960s offer a profoundly original representation of suburban angst and what was not yet known at the time as the suburban malaise. Avoiding clichés and excessively connoted referential spaces, Dard anchor these noir novels he called “novels of the night” in landscapes that are both biographical and intertextual. The West Suburbs of Paris and what was
to become the Yvelines department are at the centre of Dard’s novelistic geography, turning into a mythical and deadly space in which is negotiated an acculturation in France of the evil and ruined world described in American noir.

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Why did banking compliance fail so badly in the recent financial crisis and why, according to many, does it continue to do so? Rather than point to the lack of oversight of individuals in bank compliance roles, as many commentators do, in this paper I examine in depth the organizational context that surrounded people in such roles. I focus on those compliance personnel who did speak out about risky practices in their banks, who were forced to escalate the problem and 'whistle-blow' to external parties, and who were punished for doing so. Drawing on recent empirical data from a wider study, I argue that the concept of dependence corruption is useful in this setting, and that it can be extended to encompass interpersonal attachments. This, in turn, problematises the concept of dependence corruption because interpersonal attachments in organisational settings are inevitable. The paper engages with recent debates on whether institutional corruption is an appropriate lens for studying private-sector organisations by arguing for a focus on roles, rather than remaining at the level of institutional fields or individual organisations. Finally, the paper contributes to studies on banking compliance in the context of the recent crisis; without a deeper understanding of those who were forced to extremes to simply do their jobs, reform of the banking sector will prove difficult.

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In this paper we address the idea of ‘legal but corrupt’ through a discussion of two cases: abuse scandals in the Irish Catholic Church and the financial services industry in the wake of the Global Financial Crisis. We identify two important dynamics that generated the scandals: that they were driven by strong and stable groups existing within a peculiar kind of ‘accountability space’ that we describe as ‘monastic’ and that those groups persisted with tacit or explicit support from the state. ‘Legal but corrupt’ is, we argue, a matter of insider incomprehension sustained by the ceding of sovereignty over some aspect of social or economic life.

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Our discussion focuses on the state’s ceding administrative power to special claimants for the state’s inattention. Legal corruption, by our lights, is less about explicit or implicit exchange relationships, and more about law being employed to carve out spaces where the state actively cedes spaces to private ‘sovereigns’ – sovereigns within the space, after it has been carved out – where they can regulate themselves as they see fit and where they can project their power over others without the state stepping in.

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This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.