On the cover

G. Marx
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Abstract

tion of scale patterns assuming perfect scalability. But such success may be based on any one or more of the three bases mentioned above. Since CR is not a measure solely of scalability, it cannot be an accurate measure of scalability. That a high CR can result from the chance factor of extreme marginals has been recognized in sociological and psychological literature, and at least one political scientist has called attention to the problem. But the solution adopted has been to warn against extreme marginals and to promote an awareness of the relation between the marginals and the Guttman coefficient. For judicial cases this has meant excluding, for purposes of computing CR, all cases in which the vote of the justices has split 9-0, 8-0, 8-1, and 7-0. But this can cover up the extremeness of individuals. Moreover, any cutting point for the exclusion of cases must be arbitrarily or subjeotively chosen and thus the CR will still reflect the extremeness of whatever marginals are included. So, even if the most extreme cases are left out, the coefficient continues to reflect the magnitude of the marginals and, therefore, measures something other than scalability. An automatic correction for extremeness which avoids the subjective treatment of the problem has been devised by MenzelZ and is known as the coefficient of scalability (CS ). CS=l-E/ME, where E is total inconsistencies or errors in the scale and ME is the maximum errors possible. Maximum errors for items, ME(items) = I x N ~ ~ , ~ , . where I is the number of cases, N is the number of justices, and f,,. is the frequency of response for the modal category of a case. Maximum errors for individuals, ME(ind . )=IxN-z s where s is the subscore for the modal category of a justice. Since the coefficient of scalability measures scalability only, the ratio of CS/CR delineates that portion of the CR resulting from the factor of marginal extremeness. The level of significance for CS has been tentatively set at .60 to .65 by Menzel but, of course, this is no more objective than Guttman’s choice of -90 for a significant CR. Since in Table I we have used cases in which the marginals are as extreme as those eliminated under the standard described above, we may ask the extent to which the CR of .963 is a measure of scalability. The ME to be inserted in the formula CS = 1 E/ME is the smaller of the h4E for items and the ME for individuals, since the smaller of two maxima is the effective one. This turns out to be ME for cases, whioh in the case in question is 75. Thus CS = 1 8/75 or 394. Since this figure is considerably above the .60-.65 level and only very slightly below the .90 level we may conclude that an unusually high degree of scalability is present in our scale. We therefore reject H, for H, and conclude that the justices of the Supreme Court responded to civil liberty cases in the 1959 term in ternis of one dominant variableattitude toward deprivation of civil liberty.
封面上
假设完全可伸缩性的规模模式的组合。但这种成功可能基于上述三个基础中的任何一个或多个。由于CR不是衡量可伸缩性的唯一标准,因此它不能是衡量可伸缩性的准确标准。社会学和心理学文献已经认识到,极端边缘的偶然性因素可能导致高CR,至少有一位政治学家呼吁关注这个问题。但所采取的解决办法是对极端的边缘提出警告,并促进对边缘与古特曼系数之间关系的认识。对于司法案件,这意味着为了计算CR,排除所有法官投票结果为9比0、8比0、8比1和7比0的案件。但这可能掩盖了个人的极端。此外,排除案例的任何切点都必须是任意或主观选择的,因此,CR仍然会反映任何被包括在内的边缘的极端性。因此,即使忽略了最极端的情况,该系数仍然反映了边际的大小,因此,它衡量的是可伸缩性以外的东西。MenzelZ设计了一种避免主观处理问题的极值自动校正方法,称为可扩展性系数(CS)。CS=l-E/ME,其中E为量表的总不一致或误差,ME为可能的最大误差。项的最大错误,ME(items) = I x N ~ ~, ~,。其中I是案件的数量,N是法官的数量,f,。是一个案例的模态类别的响应频率。个人最大误差,ME(ind)=IxN-z s,其中s为正义的模态范畴的分值。由于可扩展性系数仅衡量可扩展性,因此CS/CR的比率描述了边际极值因素导致的CR部分。Menzel暂时将CS的显著性水平设定在0.60到0.65之间,但当然,这并不比Guttman选择的-90更客观。由于在表1中,我们使用的案例中,边际与在上述标准下被淘汰的案例一样极端,我们可能会问。963的CR在多大程度上是可扩展性的衡量标准。在公式CS = 1e /ME中插入的ME是项目的h4E和个人的ME中较小的一个,因为两个最大值中较小的一个是有效的。这是案例的ME,在这个案例中是75。因此CS = 1 /75或394。因为这个数字大大高于0.60 -。65级别和仅略低于0.90级别,我们可以得出结论,在我们的规模中存在异常高度的可伸缩性。因此,我们拒绝H,支持H,并得出结论,最高法院的法官在1959年任期内对公民自由案件的回应是基于对剥夺公民自由的一个主要变量的态度。
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