13 research outputs found
Is Profound Boredom Boredom?
Martin Heidegger is often credited as having offered one of the most thorough phenomenological investigations of the nature of boredom. In his 1929–1930 lecture course, The Fundamental Concepts of Metaphysics: World, Finitude, Solitude, he goes to great lengths to distinguish between three different types of boredom and to explicate their respective characters. Within the context of his discussion of one of these types of boredom, profound boredom [tiefe Langweile], Heidegger opposes much of the philosophical and literary tradition on boredom insofar as he articulates how the experience of boredom can be existentially beneficial to us. In this chapter, we undertake a study of the nature of profound boredom with the aim of investigating its place within contemporary psychological and philosophical research on boredom. Although boredom used to be a neglected emotional experience, it is no more. Boredom’s causal antecedents, effects, experiential profile, and neurophysiological correlates have become topics of active study; as a consequence, a proliferation of claims and findings about boredom has ensued. Such a situation provides an opportunity to scrutinize Heidegger’s claims and to try to understand them both on their own terms and in light of our contemporary understanding of boredom
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Can automobile insurance telematics predict the risk of near-miss events?
Telematics data from usage-based motor insurance provide valuable information –including vehicle usage, attitude towards speeding, time and proportion of urban/non-urban driving –that can be used for rate making. Additional information on acceleration, braking and cornering can likewise be usefully employed to identify near-miss events, a concept taken from aviation that denotes a situation that may have resulted in an accident. We analyze near-miss events from a sample of driversin order to identify the risk factors associated with a higher risk of near-miss occurrence. Our empirical application witha pilot sample of real usage-based insurance data reveals that certain factors are associated with a higher expected number of near-miss events, but that the association differs depending on the type of near-miss. We conclude that night time driving is associated with a lower risk of cornering events, urban driving increases the risk of braking events and speeding is associated with acceleration events. These results are relevant for the insurance industry in order to implement dynamic risk monitoring through telematics, as well as preventive actions