Copyright Issues for the Distance Learning Professor

The Internet has made the accessibility of knowledge both instantaneous and global. The professor who teaches online must be aware of the legal issues created by digital technology. The scope of the Fair Use Doctrine in the U.S. Copyright Law is under debate by educators and copyright owners. Educators advocate amending the scope of works available for distance learning, under the Fair Use principle, to include the same range of exclusions allowed in face to face classrooms such as: audiovisual works, movies and videos. While copyright owners advocate licensing of materials, educators feel that licensing procedures and costs need to be geared to the needs and ability to pay of the educational institution, otherwise their distance learning students will not have access to the same materials as those who sit in the classroom. This revised version was published online in July 2006 with corrections to the Cover Date.     

College students' electronic victimization in friendships and dating relationships: anticipated distress and associations with risky behaviors

This study investigated college students' reports of electronic victimization in friendships and dating relationships. We examined 22 items representing four categories of electronic victimization: hostility, humiliation, exclusion, and intrusiveness. Nearly all participants (92%) reported some electronic victimization in the past year, with males reporting more victimization and females anticipating more distress. Both females and males anticipated more distress from electronic victimization in dating relationships than friendships. More actual experience with electronic victimization related to lower anticipated distress. Electronic victimization was associated with females' alcohol use, even after controlling for other victimization experiences. Discussion focuses on the contextualized nature of electronic victimization, and on the importance of understanding what makes electronic victimization highly distressing for some individuals.     

Trauma Without Borders: The Necessity for School-Based Interventions in Treating Unaccompanied Refugee Minors

This article explores migration trauma among Mexican and Central American unaccompanied refugee minors (URM) with the purpose of developing an understanding of migration as a tripartite process consisting of: pre-migration exposure to traumatic stressors, in-journey stressors, and post-migration stressors. The migration experience of these youth may be subjectively different depending on a wide range of factors. The complexities of migration are explored as a traumatic, tripartite process. These three salient components of migration may act as precursors, often resulting in psychological sequelae such as: post-traumatic stress disorder (PTSD), anxiety, and depression. Of all migrant groups, URM are more likely to develop psychiatric symptoms. Trauma-Focused Cognitive Behavioral Therapy (TF-CBT), Cognitive Behavioral Intervention for Trauma in Schools (CBITS), and Mental Health for Immigrants Program (MHIP) are among the most effective interventions in the treatment of PTSD, anxiety, and depression in refugee minors. Social workers in schools are in unique positions to provide mental health services to URM. A case example illustrating a cultural adaptation of TF-CBT in an urban public high school is included. Clinical implications of culturally responsive and trauma-informed treatment of URM in schools will be discussed. Additionally, this article will emphasize the importance of bridging the gap between research and culturally responsive, trauma-informed interventions for URM in schools.     

New scrambled response models for estimating the mean of a sensitive quantitative character

Moving from the scrambling mechanism recently suggested by Saha [25 Saha, A. 2007. A simple randomized response technique in complex surveys. Metron, LXV: 59–66.  [Google Scholar]], three scrambled randomized response (SRR) models are introduced with the intent to realize a right trade-off between efficiency and privacy protection. The models perturb the true response on the sensitive variable by resorting to the multiplicative and additive approaches in different ways. Some analytical and numerical comparisons of efficiency are performed to set up the conditions under which improvements upon Saha's model can be obtained and to quantify the efficiency gain. The use of auxiliary information is also discussed in a class of estimators for the sensitive mean under a generic randomization scheme. The class includes also the three proposed SRR models. Finally, some graphical comparisons are carried out from the double perspective of the accuracy in the estimates and respondents’ privacy protection.     

Ethnic concerns and Latino party identification

The accelerated growth of the Latino population in the United States has made Latinos a coveted addition to each major political party's base. In this paper we examine the influence of ethnic concerns on the party identification of Latinos in the U.S. In contrast to previous studies, we account for Latinos’ perceptions of the political parties’ concern for their ethnic interests, allowing such interests to be self-defined. In a multinomial logit analysis of pooled data from three surveys of Latinos taken in 1999, 2004, and 2006, we find such perceptions do affect Latino partisanship, along with variables such as nativity and country of origin or ancestry. We also find a tendency toward independence among Latinos. Finally, we find movement toward the Democratic Party in 2004, once ethnic concerns are taken into account. One implication of the findings is that the party that can best persuade Latinos of their concern for their interests is the party most likely to gain their loyalties; indeed, the parties must earn those loyalties.     

A Clustering Method for Categorical Ordinal Data

Often, categorical ordinal data are clustered using a well-defined similarity measure for this kind of data and then using a clustering algorithm not specifically developed for them. The aim of this article is to introduce a new clustering method suitably planned for ordinal data. Objects are grouped using a multinomial model, a cluster tree and a pruning strategy. Two types of pruning are analyzed through simulations. The proposed method allows to overcome two typical problems of cluster analysis: the choice of the number of groups and the scale invariance.