Radical Intellectuals: What Happened to the New Urban Sociology?

This article is about the rise and fall of radicalism among 'new urban sociologists' during the 1960s and 1970s. First, I analyze the social and theoretical developments of that time and demonstrate the novelty of the questions that the new urban sociologists posed. Second, I examine the features of the practical engagements and motivations of the members of this group and show how they changed over time. Finally, I discuss the processes of institutionalization of this group. The story of the new urban sociologists is the story of members of the same generation who, dissatisfied with the development of theory in their field, developed a distinct approach to urban problems. The project that they developed combined elements of both intellectual and political projects. I consider both aspects of this project in light of Gouldner's sociology of intellectuals, and show that de-radicalization was a consequence of a peculiar combination of political disillusionment, theoretical triumph and a successful project of professionalization. Copyright Joint Editors and Blackwell Publishers Ltd 2001.

On prioritizing on-time arrivals in an outpatient clinic

<p>Non-punctual medical clinic arrivals disrupt operations, create inefficiencies, and decrease service quality. This quality improvement project examined the effects of early and late patient arrivals. We explored different queuing discipline protocols, designed to reward and to promote on-time arrival behaviors, by optimizing patient schedule management within a given clinic's workday. The goal of our study was to design a queuing system that prioritizes patients who arrive on time for their scheduled appointments, before those who are late or very early, with the assumption that a patient who arrives late or very early disrupts a clinic's desired scheduling flow. Based on data collected in a cardiology clinic at the Veterans Administration Pittsburgh Healthcare System, four simulation models were built to reflect current clinic queuing protocols, parameterizing various percentages of empty clinic appointment slots, and set to a range of acceptable patient no-show thresholds. Multi-sample statistical comparisons highlight a simulation model, utilizing an M/G/1 queuing protocol, to demonstrate significant improvements over prior models. Our proposed Hybrid protocol rewards on-time arrivals, and penalizes patients who arrive late or very early for their scheduled appointments. Clinical patient management policies that reward patients who arrive on time or slightly early may encourage patients to arrive on time for scheduled appointments and improve overall service efficiency.</p