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Autor(en): 
  • Orrin H. Pilkey
  • Linda Pilkey-Jarvis
  • Useless Arithmetic: Why Environmental Scientists Can't Predict the Future 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Januar 2007  
    Genre:  Naturwissensch., Medizin, Technik 
    ISBN:  9780231132121 
    EAN-Code: 
    9780231132121 
    Verlag:  Columbia University Press 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 231 mm / B 165 mm / D  
    Gewicht:  468 gr 
    Seiten:  248 
    Illustration:  46 illus. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    Noted coastal geologist Orrin Pilkey and environmental scientist Linda Pilkey-Jarvis show that the quantitative mathematical models policy makers and government administrators use to form environmental policies are seriously flawed. Based on unrealistic and sometimes false assumptions, these models often yield answers that support unwise policies.

    Writing for the general, nonmathematician reader and using examples from throughout the environmental sciences, Pilkey and Pilkey-Jarvis show how unquestioned faith in mathematical models can blind us to the hard data and sound judgment of experienced scientific fieldwork. They begin with a riveting account of the extinction of the North Atlantic cod on the Grand Banks of Canada. Next they engage in a general discussion of the limitations of many models across a broad array of crucial environmental subjects.

    The book offers fascinating case studies depicting how the seductiveness of quantitative models has led to unmanageable nuclear waste disposal practices, poisoned mining sites, unjustifiable faith in predicted sea level rise rates, bad predictions of future shoreline erosion rates, overoptimistic cost estimates of artificial beaches, and a host of other thorny problems. The authors demonstrate how many modelers have been reckless, employing fudge factors to assure "correct" answers and caring little if their models actually worked.

    A timely and urgent book written in an engaging style, Useless Arithmetic evaluates the assumptions behind models, the nature of the field data, and the dialogue between modelers and their "customers."

      



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