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Agenda - 04-03-2002 - 3
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Agenda - 04-03-2002 - 3
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Last modified
3/7/2017 11:25:02 AM
Creation date
8/29/2008 10:37:43 AM
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BOCC
Date
4/3/2002
Meeting Type
Work Session
Document Type
Agenda
Agenda Item
3
Document Relationships
Minutes - 20020403
(Linked To)
Path:
\Board of County Commissioners\Minutes - Approved\2000's\2002
RES-2002-022 Resolution to conduct a survey to determine feasibility of locating a Sewer Line to the Greene Tract
(Linked From)
Path:
\Board of County Commissioners\Resolutions\2000-2009\2002
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5c. Capacity Levels <br /> 5c. According to the Schools APFO and MOU the capacity levels are <br /> determined by the.School Boards and the BOCC. <br /> Recommendation 5c: The method for joint determination of capacity <br /> should be established by the BOCC and School Districts as soon as possible. <br /> 5d. Growth Projection Method <br /> 5d. The growth projection method is key for determining the future CIP <br /> and future capacity,levels under School APFO. The Tischler report <br /> conducted for the school impact fee study includes recommended <br /> projection methods for each school district. Including the Tischler <br /> method, there are five methods utilized by the BOCC. These methods <br /> are: <br /> 1. Tischler Linear (Both districts similar) <br /> 2. Orange County Planning Linear Wave <br /> 3. 10 year growth <br /> 4. 5 year Cohort survival <br /> 5. 3 year Cohort survival <br /> Using the graphs for the five methods, the staff will explain the differences <br /> among the methods. These graphs will be distributed at the meeting. <br /> Recommendation 5d: Orange County Planning Staff through discussions <br /> with the other planning directors suggest using an average of four methods <br /> to start the Schools APFO system, namely, methods 1, 2, 4, 5 above. The <br /> staff believes there is no clear pattern of accuracy with any one model at any <br /> particular school level or school district. Each subsequent year the Schools <br /> APFO technical team could analyze the trends from historical and consistent <br /> data collection and recommend which model or average better 'fits' the <br /> actual membership data. <br /> s:craiz\sluc\item5a-03132002\03-07-02\d2 <br />
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