Have Metropolitan Planning Organizations improved regional policy making? The cases of Kansas City and St. Louis.

Historically, municipalities and regions continually competed for a share of transportation funds. The process was dominated by state Departments of Transportation where cooperation, equity and participation were limited. Eighteen years ago the federal government provided metropolitan areas with the opportunity to play a larger role in the regional transportation process. On December 18, 1991 President George H.W. Bush signed the Intermodal Surface Transportation Equity Act (ISTEA). The legislation ushered in a new era of cooperation between state and local leaders by empowering regional Metropolitan Planning Organizations (MPOs). The federal legislation’s intention was to allow a region, through their MPO, to address participation, economic development, social equity and quality of life issues through their transportation policy. The significance and effectiveness of these increased functions has not been determined. The work of other scholars is insufficient to determine whether MPOs are making a difference and led to calls for further research. There was a need for an in-depth examination of MPOs through a comparative case study. This study examines whether Metropolitan Planning Organizations (MPOs) make a difference in regional transportation policy-making. It investigates whether MPOs increase public saliency, increase the consideration of social factors (e.g. employment, quality of life and equity) and improve elected official participation in the regional transportation planning process. The study examines six major regional transportation projects: Three projects at the Kansas City MPO; Mid-America Regional Council (MARC), and three projects at the St. Louis MPO; East-West Gateway Council of Governments (EWGCOG). Study results were determined through comparative analysis of the case studies. The evidence suggests MPOs make a difference in four of the five areas examined. They make a difference in public saliency, quality of life, employment factors, and elected official involvement. The means by which an MPO makes a difference include: employing expert consultants, advisory groups, and numerous internal committees brokering political agreements, and managing funds. The cases illustrate that the MPOs powers to coalesce regional cooperation are informal and that MPOs make a reasonable difference in regional transportation policy. The study points toward the need to provide more resources to MPOs

Methylchlorosilanes

The primary objective of this investigation was to prepare and improve the separation of the mono and di-methyl substituted chlorosilanes by fractional distillation

Monticello Rising

Monticello Rising is a compilation of fiction accompanied by a critical preface. The pieces within were all composed during my studies at the University of Southern Mississippi’s Center for Writers between the years of 2008-2010. The collection is about aspects of growth, initiation, and loss in human relationships

Reactions of silicon compounds with organic hydroxyl groups

Thesis (M.A.)--Boston University, 1949. This item was digitized by the Internet Archive

Bayesian Learning and Predictability in a Stochastic Nonlinear Dynamical Model

Bayesian inference methods are applied within a Bayesian hierarchical modelling framework to the problems of joint state and parameter estimation, and of state forecasting. We explore and demonstrate the ideas in the context of a simple nonlinear marine biogeochemical model. A novel approach is proposed to the formulation of the stochastic process model, in which ecophysiological properties of plankton communities are represented by autoregressive stochastic processes. This approach captures the effects of changes in plankton communities over time, and it allows the incorporation of literature metadata on individual species into prior distributions for process model parameters. The approach is applied to a case study at Ocean Station Papa, using Particle Markov chain Monte Carlo computational techniques. The results suggest that, by drawing on objective prior information, it is possible to extract useful information about model state and a subset of parameters, and even to make useful long-term forecasts, based on sparse and noisy observations