The Transition: An Historical-Materialist Perspective on Social Welfare and Social Work Practice

From an historical-materialist perspective American society is in a transition to a new structural form--a new order. The future of social welfare and social work practice is intimately bound to the nature and outcome of this transition. Moreover, the transition has economic and ideological characteristics that hold important implications for changes in the ways social workers view their clients and conduct their practice. Employing an historicalmaterialist analysis, this article will discuss the nature of the societal transition and its implications for social welfare and social work practice. The analysis will be prefaced with a synopsis of basic concepts and assumptions of the historical-materialist perspective as developed by Marx and Engles. The perspective is seen as a useful framework for assessing contemporary social work theory. The utility of the perspective for the present discussion is seen as independent of the merits and demerits of the various causes and groups labeled as or claiming to be based unon an historicalmaterialist or Marxist perspective

Not All \u27Fake News\u27 Is Equal: How Should Higher Education Respond to Fake News and in the post-Truth Era

In examining how higher education ought to respond to ‘fake news’ and the landscape of the ‘post-truth’ world, it is imperative to distinguish between accidental, ignorant, or intentional factual inaccuracies. The motives of accidental, ignorant, or disinformation are not uniform and, as such, the responses by institutions of higher education must not be uniform either. With increased literacy, as well as increased ease of publication and dissemination, the dangers of misinformation have been magnified. Stakeholders in higher education ought to develop multiple strategies responding to ‘fake news’ that are unique to the divergent forms of misinformation in the ‘post-truth’ world

Using Art to Trigger Memory, Intergenerational Learning, and Community

Abstract: This article explores the use of art to trigger memory as an effective educational tool for discussion. The author is a regular guest speaker at an affluent retirement community. The attendees are highly educated and accomplished professionals with expansive and worldly lived experiences. Formally facilitating lifelong learning, however, is a special vocation and requires a secular shared praxis and other andragogical strategies. (Keywords: photographic history, community-building, shared praxis, memory)

Mission, Faith, and Values - A Study of 94 Voices from Rhode Island Catholic Secondary School Graduates

While the mission statements of Catholic schools include strong language on faith formation, Catholic schools are more often identified with high-quality academics and less for the development of faith. A qualitative descriptive study was designed to understand how Rhode Island Catholic secondary school graduates described the influence of the Catholic educational mission on the formation of faith and personal life values. The results of the study indicate the graduates of Catholic secondary schools in Rhode Island recognized the strength of the academic programs at the four identified Catholic secondary schools. Participants also profusely described the influence of the Catholic educational mission on the development of personal life vales, but the results were less conclusive regarding graduates’ perceptions of the faith formation experience. Graduates who described faith as a process and personal journey had a more positive attitude regarding the influence of the Catholic educational mission on faith formation whereas described faith as the practice of religious ritual as well as obedience to the dogma of the Catholic Church, both positively and negatively, were less effusive regarding the Catholic educational mission

Industrial Relations and Productivity in the U.S. Automobile Industry

macroeconomics, Automobile, industrial relations, productivity

Homelessness: Residual, Institutional and Communal Solutions

Drawing upon demographic data and ethnographic interviews conducted by the authors, the article addresses the question, Who are the homeless? It identifies five kinds of homeless people and the sources of the homeless populations in the social structure. It then addresses residual and institutional policy solutions and draws on the efforts of the homeless themselves to advance a collective solution to their problems

Communicating bad news: A model for emergency mental health helpers

This article addresses the concerns of the messenger/helper who must convey tragic news to individuals and families. It offers a model to be used as a guide to ease the stress on both the deliverer and receiver of bad news. The model uses the mnemonic, PEWTER (Prepare, Evaluate, Warn, Tell, Emotional Response, Regroup), to represent the six components of the communication process

Powerful Significance Testing for Unbalanced Clusters

Clustering methods are popular for revealing structure in data, particularly in the high-dimensional setting common to contemporary data science. A central statistical question is, "are the clusters really there?" One pioneering method in statistical cluster validation is SigClust, but it is severely underpowered in the important setting where the candidate clusters have unbalanced sizes, such as in rare subtypes of disease. We show why this is the case, and propose a remedy that is powerful in both the unbalanced and balanced settings, using a novel generalization of k-means clustering. We illustrate the value of our method using a high-dimensional dataset of gene expression in kidney cancer patients. A Python implementation is available at https://github.com/thomaskeefe/sigclust.Comment: 23 pages, 11 figure

Unsupervised Machine Learning With Applications to Disease Phenotyping

This dissertation develops two methodologies in unsupervised machine learning (UL), specifically in clustering and data integration, and applies UL methodology to the investigation of phenotypes of knee osteoarthritis (KOA). First, we present novel methodology for assessing the statistical significance of clustering in the important setting of strongly unbalanced cluster sizes, which occur, for example, in the context of rare phenotypes of disease. Second, we develop a new Bayesian data integration model, which brings ideas from the frequentist data integration literature into a Bayesian setting where a posterior distribution provides rich inference and uncertainty quantification. Third, we use biclustering, a UL tool developed for gene expression data, to investigate phenotypes of KOA. Fourth, we present a data integration analysis of the common modes of variation in cartilage in KOA, based on novel cartilage thickness maps and clinical and demographic variables.Doctor of Philosoph