27 research outputs found

    A Historiometric Examination of Machiavellianism and a New Taxonomy of Leadership

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    Although researchers have extensively examined the relationship between charismatic leadership and Machiavellianism (Deluga, 2001; Gardner & Avolio, 1995; House & Howell, 1992), there has been a lack of investigation of Machiavellianism in relation to alternative forms of outstanding leadership. Thus, the purpose of this investigation was to examine the relationship between Machiavellianism and a new taxonomy of outstanding leadership comprised of charismatic, ideological, and pragmatic leaders. Using an historiometric approach, raters assessed Machiavellianism via the communications of 120 outstanding leaders in organizations across the domains of business, political, military, and religious institutions. Academic biographies were used to assess twelve general performance measures as well as twelve general controls and five communication specific controls. The results indicated that differing levels of Machiavellianism is evidenced across the differing leader types as well as differing leader orientation. Additionally, Machiavellianism appears negatively related to performance, though less so when type and orientation are taken into account.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

    AD51B in Familial Breast Cancer

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    Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possible recurrent founder mutations. In addition, we studied the known rs999737, rs2588809, and rs1314913 SNPs and RAD51B haplotypes in 44,791 breast cancer cases and 43,583 controls from 40 studies participating in the Breast Cancer Association Consortium (BCAC) that were genotyped on a custom chip (iCOGS). We identified one putatively pathogenic missense mutation c.541C>T among the Finnish cancer patients and subsequently genotyped the mutation in additional breast cancer cases (n = 5259) and population controls (n = 3586) from Finland and Belarus. No significant association with breast cancer risk was seen in the meta-analysis of the Finnish datasets or in the large BCAC dataset. The association with previously identified risk variants rs999737, rs2588809, and rs1314913 was replicated among all breast cancer cases and also among familial cases in the BCAC dataset. The most significant association was observed for the haplotype carrying the risk-alleles of all the three SNPs both among all cases (odds ratio (OR): 1.15, 95% confidence interval (CI): 1.11–1.19, P = 8.88 x 10−16) and among familial cases (OR: 1.24, 95% CI: 1.16–1.32, P = 6.19 x 10−11), compared to the haplotype with the respective protective alleles. Our results suggest that loss-of-function mutations in RAD51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk

    Representation in the (Artificial) Immune System

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    Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausible dynamical systems, with little overlap between. We propose that this dichotomy is somewhat to blame for the lack of significant advancement of the field in either direction and demonstrate how a simplistic interpretation of Perelson’s shape-space formalism may have largely contributed to this dichotomy. In this paper, we motivate and derive an alternative representational abstraction. To do so we consider the validity of shape-space from both the biological and machine learning perspectives. We then take steps towards formally integrating these perspectives into a coherent computational model of notions such as life-long learning, degeneracy, constructive representations and contextual recognition—rhetoric that has long inspired work in AIS, while remaining largely devoid of operational definition

    Deforestation and capital accumulation: lessons from the Upper Kerinci region, Indonesia

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    This study outlines a case where the behaviour of farmers in accumulating capital, rather than their poverty as commonly assumed, results in deforestation. Fieldwork was undertaken in the Upper Kerinci region of the island of Sumatera, Indonesia. A financial analysis of the "net income" streams received by farmers from deforestation is performed. Because forest lands can be "captured " and privatised through clearing and the subsequent agriculture have the capacity to produce high financial returns for farmers as well as to provide adequate capital to finance the next forest clearing. Such a capacity enables landless farmers to become land owners. Forest clearing also enables farmers to own a "long-term maturity bond" in the form of a cinnamon plantation. Poverty precludes poorer farmers from deforestation, and decisions to clear a forest rest mostly with more established farmers. Financial surpluses from outside the forestry and agricultural sectors are also used to finance forest clearing
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