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A Complete Streets Analysis and Recommendations Report for the City of Bakersfield, CaliforniaGeorge, Sherie L 01 June 2013 (has links) (PDF)
Driven by California State legislation, the City of Bakersfield is taking steps to introduce Complete Streets to the community. Working in collaboration with the Bakersfield City Planning Department, this project was prompted by the CIty's forthcoming update of its Metropolitan Bakersfield General Plan Circulation Element, with purpose to meet the California Complete Streets Act (AB1358) requirement to plan for a balanced, multimodal transportation network. This professional project intends to provide Bakersfield city officials, staff, and residents with tools and information needed to assess and implement Complete Streets within the Community.
The project provides in depth background research on the Complete Street concept, related legislation, design features, and benefits. It reviews three Complete Street projects from similar cities located in the Central Valley with purpose to deliver guiding principles Bakersfield can utilize for successful implementation. The project provides new conceptual street standards with recommended design feature tables based on existing street types. In conclusion, this project evaluated the newly adopted Bakersfield Complete Street Policy through a strategic approach with final recommendations to build a stronger Complete Street network.
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The formation of zoned metasomatic veins and massive skarn in dolomite, southern Sierra Nevada, CaliforniaMyers, Bruce Eric, 1956- January 1988 (has links)
No description available.
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Predicting first-time freshman persistence at California State University, Bakersfield: Exploring a new modelRadney, Ron 01 January 2009 (has links) (PDF)
Institutions of higher education invest a significant amount of resources in recruiting, processing, and advising new students. When students leave the institution prior to graduation, the university loses considerable revenues. Therefore, it is important for colleges and universities to refine their student recruitment and retention strategies to avoid forgone revenues by predicting which students are likely to need particular types of support services (DeBerard et al, 2004). Current models of prediction utilize extensive surveys that are impractical to administer each term, and they do not adequately identify the broad range of student persistence categories needed in order to gain a greater understanding of persistence behavior (Davidson, 2005; Porter, 2000; Tinto, 1975). This study created a linear discriminant function to predict a broad range of persistence levels of first-time freshmen students at California State University, Bakersfield (CSUB), by identifying pre-enrollment and early enrollment student variables that existed within the database of the University. This information may be used to develop support service strategies to better assist incoming students predicted to have a greater probability of not persisting.
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