Capital Collaboration: An In-Depth Look at the Community Investment System in Massachusetts Working Cities

This publication presents the work of the Capital & Collaboration Initiative, a cross-sector effort designed to increase the scale, efficiency and impact of investments in Massachusetts cities of more than 35,000 people (excluding Boston), characterized by below-median family income and above-average poverty rates, which have been termed "Working Cities" by the Federal Reserve Bank of Boston.In 2013, the Boston Fed launched the Working Cities Challenge, a competition designed to incentivize cross-sector leadership and collaboration to benefit low- and moderate-income residents in these cities.In 2015, the Fed launched Capital & Collaboration as a companion process, examining the delivery of capital for downtown revitalization, small business, and scattered-site residential development. The Fed convened a working group of stakeholders from institutions that provide capital and services to communities in the Working Cities. It then invited Kresge Foundation Senior Fellow Robin Hacke and Katie Grace of the Initiative for Responsible Development to work with these parties to examine the community investment system, drawing on a capital-absorption framework Hacke and Grace had developed and have applied in cities across the country

Book review: ghostbodies: towards a new theory of invalidism by Maia Dolphin-Krute

In Ghostbodies: Towards a New Theory of Invalidism, Maia Dolphin-Krute explores depictions of chronic illness, proposing the idea of the 'ghostbody' as a means of understanding both its representation and potential. While the writing style and lack of concrete examples may at times limit the ability of scholars to transfer its concepts to other disciplines, Matthew Hacke welcomes this book as an exciting and broadly unique contribution to the study of cultural constructions of illness and disability

Church, Space and Conflict: Religious Co-Existence and Political Communication in Seventeenth-Century Switzerland

This article sets out to explore how a local quarrel in the Grafschaft of Baden, a bi-confessional Swiss county, occasioned by efforts to install a separate font for Protestant parishioners, activated larger constitutional and confessional tensions between the Catholic and Protestant cantons of the Swiss Confederation. The article reconstructs the lengthy political negotiations caused by the rearrangement of church space since the Landfrieden of 1531: this treaty had enshrined bi-confessionalism in the Swiss Confederation and had established the duties and rights of both confessions, although to the disadvantage of the Reformed Protestants. It had also transformed the consecrated space of the church into a stage for political action by the cantons. From 1531 onwards, changes in religious belief and observance were subject to the will of the supreme governing authority. The article shows that local conflicts over the arrangement and furnishing of certain church spaces can give us fascinating insights into political practice, the establishment of social order and the handling of denominational differences within the Swiss Confederation. It attempts to contribute to our understanding of early modern political history by using concepts from cultural history and communication theory in which politics is closely linked to social and confessional processes generating meaning and orde

Book review: poor news: media discourses of poverty in times of austerity by Steven Harkins and Jairo Lugo-Ocando

In Poor News: Media Discourses of Poverty in Times of Austerity, Steven Harkins and Jairo Lugo-Ocando explore how debates and discourses surrounding poverty and welfare have been shaped by the mainstream press in the UK. The granular content analysis offered by the book gives great insight into the normalisation of social inequality across the British media landscape, writes Matthew Hacke, and will be of interest to those looking to formulate a more ethical and inclusive journalism

Die Wissensgesellschaft und die Bildung des Subjekts - ein Widerspruch?

Der Beitrag untersucht, inwiefern sich medienpädagogisch relevante Diskrepanzen zwischen dem Diskurs der Wissensgesellschaft und jugendlichem Medienhandeln nachzeichnen lassen. Dazu werden zunächst einige Aspekte des Konstrukts Wissensgesellschaft skizziert, das in seiner gegenwärtig populären Form ins Fahrwasser an volkswirtschaftlichen Verwertungskalkülen orientierter Denkformen geraten ist. Dies wird in Bezug auf die sich daran gekoppelte Programmatik von Kompetenz diskutiert, welche den «homo oeconomicus» beschwört und sich darin konträr zu klassisch bildungstheoretischen Kategorien verhält. Weitergeführt werden diese Überlegungen anhand der Problematisierung des Medienkompetenztheorems, das sich bis heute damit schwer tut, sich von der Vereinnahmung durch zweckrationale und restringierende Tendenzen zu befreien. Argumentiert wird, dass mit Medienkompetenz zu wenig einer milieuspezifischen Differenzierung Rechnung getragen werden kann, die eine wichtige Prämisse für eine soziale Ungleichheiten ernst nehmende Medienpädagogik ist. Als eine Alternative diskutieren wir, inwieweit sich hier praxeologische Perspektiven zum Verständnis jugendlichen Handelns anbieten. Der Beitrag mündet in einige medienpädagogisch fruchtbare Ideen, in deren Zentrum eine reflexivere, stärker am Habitus von Jugendlichen orientierte Praxis steht

The Role of Fiction Courses in College Curricula

A survey submitted by Robert E. L. Hacke to the Faculty Research Committee on June 30, 1970 on the extent to which fiction courses are included in the curriculum of colleges and universities

Using decision-tree classifier systems to extract knowledge from databases

One difficulty in applying artificial intelligence techniques to the solution of real world problems is that the development and maintenance of many AI systems, such as those used in diagnostics, require large amounts of human resources. At the same time, databases frequently exist which contain information about the process(es) of interest. Recently, efforts to reduce development and maintenance costs of AI systems have focused on using machine learning techniques to extract knowledge from existing databases. Research is described in the area of knowledge extraction using a class of machine learning techniques called decision-tree classifier systems. Results of this research suggest ways of performing knowledge extraction which may be applied in numerous situations. In addition, a measurement called the concept strength metric (CSM) is described which can be used to determine how well the resulting decision tree can differentiate between the concepts it has learned. The CSM can be used to determine whether or not additional knowledge needs to be extracted from the database. An experiment involving real world data is presented to illustrate the concepts described

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base