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Articles 1 - 3 of 3
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Household Intimacy And Being Unmarried: Family Pluralism In The Novels Of Anthony Trollope, Linda C. Mcclain, Allison Anna Tait
Household Intimacy And Being Unmarried: Family Pluralism In The Novels Of Anthony Trollope, Linda C. Mcclain, Allison Anna Tait
Faculty Scholarship
Many critics rightfully claim that the marriage market and an inquiry into its innermost workings are at the heart of Anthony Trollope’s novels, but this Article argues that his novels also depict—on the periphery or sometimes just hiding in plain sight—a set of curiously nonmarital households. These households vary in form, but include widows and widowers living on their own, mothers and daughters living collectively, and male cousins sharing space and the work of daily living. Critics have debated whether Trollope was simply a realistic social historian—chronicling families as he found them— or whether he constructively used literary license to …
What Mcculloch V. Maryland Got Wrong: The Original Meaning Of 'Necessary' Is Not 'Useful', 'Convenient', Or 'Rational', Steven Calabresi, Gary S. Lawson, Elise Kostial
What Mcculloch V. Maryland Got Wrong: The Original Meaning Of 'Necessary' Is Not 'Useful', 'Convenient', Or 'Rational', Steven Calabresi, Gary S. Lawson, Elise Kostial
Faculty Scholarship
McCulloch v. Maryland, echoing Alexander Hamilton nearly thirty years earlier, claimed of the word “necessary” in the Necessary and Proper Clause: “If reference be had to its use, in the common affairs of the world, or in approved authors, we find that it frequently imports that one thing is convenient, or useful . . . to another.” Modern case law has translated that understanding into a rational-basis test that treats the issue of necessity as all but nonjusticiable; The Supreme Court has never found a congressional law unconstitutional on the ground that it was not “necessary . . . …
Trial Selection And Estimating Damages Equations, Keith N. Hylton
Trial Selection And Estimating Damages Equations, Keith N. Hylton
Faculty Scholarship
Many studies have employed regression analysis with data drawn from court opinions. For example, an analyst might use regression analysis to determine the factors that explain the size of damages awards or the factors that determine the probability that the plaintiff will prevail at trial or on appeal. However, the full potential of multiple regression analysis in legal research has not been realized, largely because of the sample selection problem. We propose a method for controlling for sample selection bias using data from court opinions.