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Urban Planning 206A Prof. Leo Estrada By Pedro E. Nava

Fresno County & The San Joaquin Valley: Agricultural Production, Unemployment, & Educational Attainment . Urban Planning 206A Prof. Leo Estrada By Pedro E. Nava. San Joaquin Valley Comprised of 8 counties Considered the agricultural hub of the state & nation . Measure of America

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Urban Planning 206A Prof. Leo Estrada By Pedro E. Nava

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  1. Fresno County & The San Joaquin Valley: Agricultural Production, Unemployment, & Educational Attainment Urban Planning 206A Prof. Leo Estrada By Pedro E. Nava

  2. San Joaquin Valley Comprised of 8 counties Considered the agricultural hub of the state & nation. Measure of America (2008) SJV is one of the lowest ranked regions on wellbeing indicators. [Health, Income, Education]

  3. The Purpose • To analyze spatial relationships between agricultural production, poverty and educational attainment. • How does the political economy of the San Joaquin Valley shape the life chances of youth living there? • Where are there areas in the SJV that foster greater opportunity for youth, specifically those from farmworkingbackgrounds?

  4. California & The Migrant Labor • $36.2 billion agricultural output in state of CA (2008) (CA Dept. of Food & Ag) • $11.3 billion alone in counties that are part of U.S. CD 20 (Measure of America) • Measure of America report • CD 20 rated worst in the nation out of 435 • Only 6.5% of adults were college graduates • Average income $17K year

  5. A Profile of Migrant Students • 800,000 migrant students nationally • 330,000 in California • Almost 45% live in Central Valley • (US. Dept of Education, 2003) • Large percentages of students are undocumented.

  6. SJV is #1 in Ag Production • Historical development of state allowed for the creation of large farms in CA. • Yet US farm policy is based on “small family” farm of Midwest. • Fresno County has higher than state average unemployment rate • Stats underestimate the real unemployment rate due to seasonal status of farm labor demands & residency status of farmworkes today.

  7. Racial Makeup of SJV

  8. To determine the poverty rate of youth under 18 in Fresno County I combined attribute fields from the American Community Survey for males and females . [(<5) + (5) +(6-11) + (12-14) + (15) + ( 16-17)] Male * Female = The westside of Fresno County has the higher percentages of youth in poverty. It also has the higher percentages of farmworkers living there.

  9. Educational Attainment of Males and Females in Fresno County • These maps are a comparison of Males and females over 25 years of age who have attained at least a college degree • It is not surprising to note that lower levels of college degree attainment are present on the westside, the area with the highest percentages of youth in poverty. What is the likelihood that the youth from there will have a different trajectory then adults from there community?

  10. Educational attainment of White & Latino males by Median Household Income. • The two insets are Metro Areas of: • Fresno • Bakersfield • As is evident, no one census tract has more than 13% of college grads.

  11. I Geocoded schools that fit 2 criteria. • Had high API scores (over 800) • or • High percentages of Latinos (at least 70%) and high percentages of EL and migrant students • Only Waterford High had

  12. I developed this layout as a case study. How does lack of accessible transportation limit the abilities of (im)migrant families living in rural communities to engage in the schooling of their children? Parent engagement is linked in educational research as a key factor for student success. • Buffers are 12 mile radius

  13. Small things go a long way • According to Phil Martin 40 percent increase in farm worker wages passed to consumers • Would cost $16 a year • Yet, average Farmworker earnings for a seasonal worker would increase by $4000 to $13,600 • That would put them $3,200 over the poverty line (Phil Martin, 2010)

  14. Utilization of Metadata

  15. Model’s Used Clipped California Streets to San Joaquin Valley

  16. Skills that were utilized • Inset Map • Aggregate attribute fields • Clipping • Modeling • Geocoding • Metadata • Original data • Charts & Graphs • Point/line graduated symbols

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