Relevant bibliographies by topics / Maricopy County

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Maricopy County'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Maricopy County"

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Goldman, Robert. "Applying PPO Theory in Maricopa County." Health Marketing Quarterly 2, no. 2-3 (April 1985): 135–44. http://dx.doi.org/10.1300/j026v02n02_13.

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Polman, George V. "Potter-Cramer Mine, Maricopa County, Arizona." Rocks & Minerals 96, no. 1 (December 22, 2020): 24–37. http://dx.doi.org/10.1080/00357529.2021.1827908.

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Roy, Avipsa, Trisalyn A. Nelson, A. Stewart Fotheringham, and Meghan Winters. "Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists." Urban Science 3, no. 2 (June 4, 2019): 62. http://dx.doi.org/10.3390/urbansci3020062.

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Traditional methods of counting bicyclists are resource-intensive and generate data with sparse spatial and temporal detail. Previous research suggests big data from crowdsourced fitness apps offer a new source of bicycling data with high spatial and temporal resolution. However, crowdsourced bicycling data are biased as they oversample recreational riders. Our goals are to quantify geographical variables, which can help in correcting bias in crowdsourced, data and to develop a generalized method to correct bias in big crowdsourced data on bicycle ridership in different settings in order to generate maps for cities representative of all bicyclists at a street-level spatial resolution. We used street-level ridership data for 2016 from a crowdsourced fitness app (Strava), geographical covariate data, and official counts from 44 locations across Maricopa County, Arizona, USA (training data); and 60 locations from the city of Tempe, within Maricopa (test data). First, we quantified the relationship between Strava and official ridership data volumes. Second, we used a multi-step approach with variable selection using LASSO followed by Poisson regression to integrate geographical covariates, Strava, and training data to correct bias. Finally, we predicted bias-corrected average annual daily bicyclist counts for Tempe and evaluated the model’s accuracy using the test data. We found a correlation between the annual ridership data from Strava and official counts (R2 = 0.76) in Maricopa County for 2016. The significant variables for correcting bias were: The proportion of white population, median household income, traffic speed, distance to residential areas, and distance to green spaces. The model could correct bias in crowdsourced data from Strava in Tempe with 86% of road segments being predicted within a margin of ±100 average annual bicyclists. Our results indicate that it is possible to map ridership for cities at the street-level by correcting bias in crowdsourced bicycle ridership data, with access to adequate data from official count programs and geographical covariates at a comparable spatial and temporal resolution.
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JAYCOX, SHARON H., and SABINA PAGLIALUNGA. "Rate of Diabetes in Maricopa County, AZ." Diabetes 67, Supplement 1 (May 2018): 1651—P. http://dx.doi.org/10.2337/db18-1651-p.

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Berisha, Vjollca, David Hondula, Matthew Roach, Jessica R. White, Benita McKinney, Darcie Bentz, Ahmed Mohamed, Joshua Uebelherr, and Kate Goodin. "Assessing Adaptation Strategies for Extreme Heat: A Public Health Evaluation of Cooling Centers in Maricopa County, Arizona." Weather, Climate, and Society 9, no. 1 (December 21, 2016): 71–80. http://dx.doi.org/10.1175/wcas-d-16-0033.1.

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Abstract Preventing heat-associated morbidity and mortality is a public health priority in Maricopa County, Arizona (United States). The objective of this project was to evaluate Maricopa County cooling centers and gain insight into their capacity to provide relief for the public during extreme heat events. During the summer of 2014, 53 cooling centers were evaluated to assess facility and visitor characteristics. Maricopa County staff collected data by directly observing daily operations and by surveying managers and visitors. The cooling centers in Maricopa County were often housed within community, senior, or religious centers, which offered various services for at least 1500 individuals daily. Many visitors were unemployed and/or homeless. Many learned about a cooling center by word of mouth or by having seen the cooling center’s location. The cooling centers provide a valuable service and reach some of the region’s most vulnerable populations. This project is among the first to systematically evaluate cooling centers from a public health perspective and provides helpful insight to community leaders who are implementing or improving their own network of cooling centers.
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Gourley, Ruth L. "TRENDS IN CUSTODY STUDIES, MARICOPA COUNTY, ARIZO, 1972-1975." Family Court Review 13, no. 1 (April 4, 2005): 14–17. http://dx.doi.org/10.1111/j.174-1617.1975.tb00750.x.

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Kenny, Brian, and Vince Murray. "Creating Competent Customers of Historic Preservation." Practicing Anthropology 25, no. 4 (September 1, 2003): 19–22. http://dx.doi.org/10.17730/praa.25.4.d317r0w720t96514.

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Maricopa County Arizona is home to about 3.5 million people who live in 24 incorporated cities and towns and 32 unincorporated communities. It is a place with a mix of people, most of who have come from somewhere else, but it also includes individuals and families who have been on the land for generations. The popular, global media vision holds that the communities of Maricopa County, notably metropolitan Phoenix and its suburbs, were built yesterday, and that everything is new and fresh. It is thought of as a place to engage several grand American traditions: arrival, starting over, self-reinvention, financial establishment through real estate investment, and active retirement.
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Taylor, Melanie M., Tom Mickey, Katherine Browne, Kerry Kenney, Bob England, and Lily Blasini-Alcivar. "Opportunities for the Prevention of Congenital Syphilis in Maricopa County, Arizona." Sexually Transmitted Diseases 35, no. 4 (April 2008): 341–43. http://dx.doi.org/10.1097/olq.0b013e31815bb335.

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Iverson, Sally Ann, Jigna Narang, Melissa J. Garcia, James Matthews, Nicole Fowle, Jennifer Collins, Sumathi Ramachandran, et al. "Hepatitis A Outbreak Among Persons Experiencing Homelessness—Maricopa County, Arizona, 2017." Open Forum Infectious Diseases 4, suppl_1 (2017): S245. http://dx.doi.org/10.1093/ofid/ofx163.525.

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Fulginiti, Laura C. "Fatal Footsteps: Murder of Undocumented Border Crossers in Maricopa County, Arizona." Journal of Forensic Sciences 53, no. 1 (January 2008): 41–45. http://dx.doi.org/10.1111/j.1556-4029.2007.00613.x.

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Dissertations / Theses on the topic "Maricopy County"

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Hussain, Jawad. "Reproductive Life Planning in the Refugee Community: Focus on the Role of Men and Religion." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/623441.

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A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.
Health literacy is the degree to which individuals have the capacity to understand basic health information and services needed to make appropriate health decisions. Women seen at Maricopa Integrated Health System (MIHS) Refugee Women’s Health Clinic (RWHC) are routinely offered education on developing a Reproductive Life Plan (RLP). In order to influence women’s reproductive health and medical decision‐making, there is a need to tailor RLP counseling to engage their male partners in the refugee community. We aimed to assess increased knowledge on preconception care related to the importance of developing a RLP, perspectives on birth spacing, and the influence of men as well as religion in medical decision‐making. We aimed to identify the refugee community’s receptivity to culturally and linguistically appropriate audiovisual modalities. Study participants comprised 120 refugees (39 men and 81 women) including couples, across the respective target languages with pre‐ and post‐Likert scale surveys assessing perspectives on RLP, birth spacing, the role of religion, and readiness for behavior change. Summary statistics examined changes in pre‐ and post‐Likert scale survey responses with responses dichotomized as Strongly agree/Agree compared against all other responses. A higher frequency of male respondents agreed about knowing what RLP means in the posttest relative to pretest (71.8% to 89.7%, P = 0.016) as well as 'Not having children…' (41% to 64.1%, P=0.035). Female respondents were more likely to agree to 'Know what RLP means' (76.5% to 86.4%, P =0.039) and 'Having a baby soon after…' (65.4% to 76.5%, P =0.035) after the training. They also were less likely to agree that 'RLP is about birth control' (71.6% to 59.3%, P =0.021). Amongst Muslim participants, we found improvement in knowing what RLP means (65.5% to 87.9%) and that it is important for men to have a RLP (67.2% to 84.5%). Cronbach’s alpha was used to measure internal inconsistency, with most values less than 0.5 and deemed unacceptable. Only one value, birth spacing, was > 0.6 and deemed questionable. There was the same degree of concordance, yet there also was discordance in the direction of opinions between women and men pre vs post‐test answers. When comparing couples pre and posttest, there was no significant differences observed across genders. This is the first reported U.S. initiative to provide a culturally and linguistically appropriate preconception health education. Project had demonstrated ability to mobilize several ethnic communities around the RLP. Respondents among both genders were more likely to agree about knowing what RLP means. The most challenging aspect of our community mobilization efforts was recruiting a larger sample size. Another limitation was the use of the Likert scale in a population with low literacy as there were some discrepancies in responses to negatively‐worded questions. Future studies could use a visual analog scale of smiley faces to assist those with limited literacy and incorporate a more global feel.
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El-Haris, Mamdouh Khamis. "Soil spatial variability: Areal interpolations of physical and chemical parameters." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184290.

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Four fields of 117 ha area located at the University of Arizona's Maricopa Agricultural Center were selected for this study. Two soil series, the Casa Grande sandy clay loam and Trix clay loam occur. Surface samples (0-25 cm) were collected on a 98 m interval and 3 rows providing 47 sites per field. Sites were classified either as surveying (32) or testing (15) in each of the four fields. Additional samples at 25-50, 50-75, 75-100, and 100-125 cm were obtained with duplicate surface undisturbed cores at 5 sites per field. Soil parameters include bulk density, saturated hydraulic conductivity, moisture retention, particle size analysis, pH, EC, soluble cations, SAR, and ESP. A quantification of the spatial interdependence of samples was developed based on the variogram of soil parameters. A linear model was best fitted to the clay, EC, Ca²⁺, Mg²⁺, Na⁺, SAR and ESP, and a spherical model to the sand, silt, pH, and K⁺ observed variograms. A comparison of variograms obtained conventionally and with the robust estimation of Cressie and Hawkins (1980) for sand and Ca²⁺ were performed with a fixed couples number per class and with a fixed class size. Additionally, a negative log-likelihood function along with cross-validation criteria were used with the jackknifing method to validate and determine variogram parameters. Three interpolation techniques have been compared for estimating 11 soil properties at the test sites. The techniques include Arithmetic Mean, Inversely Weighted Average, and Kriging with various numbers of neighbor estimates. Using 4 point estimates resulted in nearly identical results, but the 8 point estimates gave more contrast for results among the alternative techniques. Jackknifing was used with 4, 8, 15, 25 neighbors for estimating 188 points of sand and Ca²⁺ with the three techniques. Sand showed a definite advantage of Kriging by lowering the Mean Square Error with increasing neighbor number. The simple interpolator Arithmetic Mean was comparable and sometimes even better than the other techniques. Kriging, the most complex technique, was not the absolute best interpolator over all situations as perhaps expected. The spatial dependence for the 11 soil variables was studied by preparing contour maps by punctual Kriging. Sand and Ca²⁺ were also mapped by block Kriging estimates.
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Suliman, Ahmed Saeid Ahmed. "Spectral and spatial variability of the soils on the Maricopa Agricultural Center, Arizona." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184678.

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Dry and wet fine earth spectral measurements were made on the Ap soil surface horizons on the Maricopa Agricultural Center by using a Barnes Modular Multiband Radiometer. Three subsets were used in the analyses 552, 101 and 11. There were three soil series, Casa Grande, Shontik and Trix, four soil mapping units, and three texture classes identified on the farm. The wet soil condition reduced the amplitude of the spectral curves over the entire spectrum range (0.45 to 2.35 μm). The spectral curves were statistically related to the soil mapping units to determine if the soil mapping units and texture classes could be separated. The wet soil condition and the smaller sample size increased the correct classification percentages for soil mapping units and texture classes. LSD tests showed there were significant differences between these groups. Simple- and Multiple-linear regression analysis were used to relate some soil physical (sand, silt and clay contents and color components) and chemical (iron oxide, organic carbon and calcium carbonate contents) to soil spectral responses in the seven bands under dry and wet conditions. There were high correlations levels among the spectral bands showing an overlap of spectral information. Generally, the red (MMR3) and near-infrared (MMR4) bands had the highest correlations with the studied soil properties under dry and wet conditions. Usually, the wet soil condition resulted in higher correlations than that for the dry soil condition over the total spectrum range. The predictive equations for sand, silt and clay and iron oxide contents were satisfactory. For organic carbon and color components, the greatest success was achieved when variation in spectral response within individual samples are smaller than that between soil mapping unit group averages. There was a poor relation between calcium carbonate and spectral response. A comparison of multi-level remotely sensed data collected by SPOT, aircraft, and ground instruments showed a strong agreement among the data sets, which correlated well to fine earth data, except for the SPOT data. Rough soil surfaces showed a reduction in reflectance altitude compared to laser level, and it appears to be directly proportional to the percent shadow in the viewing area measured by SPOT satellite and aircraft.
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Dawson, Lester, and David K. Parsons. "Alfalfa Variety Trial, Maricopa County." College of Agriculture, University of Arizona (Tucson, AZ), 1985. http://hdl.handle.net/10150/200499.

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Massimo, Lauren. "Celiac Disease in the Hispanic Population at Maricopa Integrated Health System." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/623603.

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A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.
Celiac disease (CD) is an autoimmune gastrointestinal disorder that has been well studied amongst non‐Hispanic white populations. Data specifically describing the disease in the U.S. Hispanic population is limited and available studies that do report prevalence and incidence within this population reveal discrepancies. The aim of this study is to estimate the incidence of CD and to define common presenting symptoms in Hispanics in Phoenix, AZ. Data was collected via a retrospective chart review from Maricopa Integrated Health System (MIHS), an organization caring for a patient population that is >50% Hispanic, between 2004‐2013. The study population is both adult and pediatric patients that had received the ICD‐9 code 579.0. The total number of non‐repeat patients seen at MIHS each year between 2004‐2013 was also determined and broken down by race for incidence calculations. During this 10‐year period, 29 total patients were diagnosed with CD at MIHS. The overall yearly incidence increased from 1 in 44,011 patients in 2004 to 1 in 27,948 in 2013. Of the 29 diagnosed, 52% were Caucasian, 34% Hispanic, 7% Asian and 7% African American. The yearly incidence in Hispanic patients also increased from 0 in 2004 to 1 in 58,302 in 2007 to 1 in 25,826 in 2013. Although diagnosis was greater in females of both races, Hispanic patients were diagnosed at a younger age than Caucasians (22 vs. 31 y/o, respectively). The most common diagnostic approach was serological testing combined with duodenal biopsy. The 3 most common gastrointestinal presenting symptoms in Caucasians were diarrhea, abdominal pain and nausea/vomiting, while those in Hispanics were constipation, bloating/abdominal distention and diarrhea. At the time of diagnosis, at least 1/3rd of both Caucasian and Hispanic patients had presented with another autoimmune disorder. Other associated conditions were neurological symptoms and iron‐deficiency anemia. Data from this study suggests that CD in the Hispanic population may be more common in Phoenix than the overall population in the U.S. as described in the literature. It also suggests that Hispanic patients may have different presenting symptoms than do Caucasians. The reason behind the increase in CD incidence in Hispanics is unclear, although increased physician awareness and diagnosis may play a role. Further research and awareness of CD in the Hispanic population may be necessary to optimize diagnosis & treatment of the condition.
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Young, Kelly Murray, and Kai Umeda. "Vegetable Planting Calendar for Maricopa County." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2010. http://hdl.handle.net/10150/144780.

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4 pp.
Based upon original work by: Lucy Bradley and Kai Umeda; April 1998
Maricopa County is a wonderful place to garden. Almost any type of vegetable or fruit can be grown successfully provided one chooses appropriate varieties and plants at the right time. This publication is a detailed garden planting calendar for selected fruits and vegetable in Maricopa County, Arizona. It also briefly discusses the climate, season, and potential pests which would impact the selection of the vegetables.
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Mayorga, Maria Irles 1943. "Economic impacts of salinization in irrigated agricultural land : an Arizona case study." Diss., The University of Arizona, 1988. http://hdl.handle.net/10150/191135.

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The dynamics of salt accumulation in the soil over time is one of major important information input needed for decision-making in regard to irrigate with saline water. As all waters contain some dissolved salts, during the irrigation these salts tend to concentrate in the soil causing depressed plant growth. Saline irrigation water, low soil permeability, inadequate drainage conditions, low rainfall and poor irrigation management all contribute to the tendency of salt accumulation in the soil. The principal salt accumulation problem of economic importance arises when non-saline soils become saline as result of irrigation. The dynamics of salt accumulation in this study, is based on the model for tracing salt distribution in the soil affected by the quantity and quality of irrigation water, amount of nitrogen and initial soil salinity. To verify the model for tracing salt distribution in the soil and to statistically estimate a crop-production function and soil salinity relation, agronomic data were used from field experiment conducted at the University of Arizona, Maricopa Agricultural Center (MAC), during the 1985 growing season and that utilized cotton variety Delta Pine 61. From the point of view of the response functions and salt accumulation in the soil, many assumptions were made before formulating the models. Results show that (1) no conclusions could be drawn with respect to the model of salt accumulation in the soil, (2) in the case of yield production function and soil salinity relation, the water quantity coeffient had an absolute value greater than one, (3) water quality and nitrogen coefficients had an absolute value less than one, (4) initial soil salinity coefficient had negative value, (5) looking for the best combination amoung the variables inputs, the marginal rate of substitution was greater than the ratio of prices, (6) the time path for soil salinity converge to a steady state conditions, and (7) the profitability of cotton irrigated with drip system is sensitive to yield increases and increases in the price of cotton.
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Graham, Aaron Robert. "In Situ Characterization of Unsaturated Soil Hydraulic Properties at the Maricopa Environmental Monitoring Site." Thesis, The University of Arizona, 2004. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_etd_hy0005_m_sip1_w.pdf&type=application/pdf.

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Breslauer, Cori Ann. "TRENDS IN CHLAMYDIA TRACHOMATIS INFECTION IN MARICOPA COUNTY ADOLESCENTS, 2006‐2010." Thesis, The University of Arizona, 2015. http://hdl.handle.net/10150/348453.

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Nelson, Erin Da‐Hye. "Evaluation of an Opt-Out HIV Screening Program in the Maricopa County Jails." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/623513.

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A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.
Since inmates are a population disproportionately affected by HIV, correctional settings are important sites for delivering HIV services. The Maricopa county (Phoenix Area) jail system is the 4th largest in the nation. In 2011, the Maricopa County Correctional Health Service implemented an opt‐out HIV screening program for individuals booked into the Maricopa County Jails (MCJ). The aims of this study were to determine for the years 2012‐2014: • The number of inmates screened for HIV • The HIV positivity rate • The number of newly diagnosed patients • The clinical characteristics of the newly diagnosed HIV positive patients Five to seven days after booking, inmates are offered HIV screening. These laboratory records were used to determine the number of inmates tested and positivity. Prior history of previous HIV diagnosis was obtained from Maricopa public health records. Retrospective chart review of the MCJ health and case management records, including Ryan White forms, was performed to gather gender, age, race/ethnicity, sexual orientation, drug use, homelessness and co‐morbidities of newly HIV‐infected persons, such as Hepatitis C and prior STDs. Categorical factors were compared between groups with the Chi‐square test. Means were compared using a standard t test. P values ≤0.05 were considered significant. A total of 319,575 persons were booked and 46,346 were screened (14.5%) for HIV during the study period. The majority of booked inmates were male (76.9%) and Caucasian (50.8%). The mean age of inmates was 36 years. There were 70 newly HIV‐diagnosed patients. Chi squared and t tests comparing newly diagnosed individuals to the general jail population revealed statistical significance for male gender (p=0.02), African American race (p=0.04), and age (p=0.003). Undiagnosed HIV, including AIDS (CD4 counts <200), is an important issue among individuals booked into the MCJ. Compared to the general jail population, HIV is more likely to be diagnosed in males rather than females, younger patients, and African‐American patients. Additionally, IV drug use, polysubstance abuse, other STDs (particularly syphilis), high risk sexual activity, Hepatitis C and homelessness were common among HIV positive patients. Surveillance should be continued and include more patient education on the importance of screening. Furthermore, targeting high‐risk populations may result in even greater numbers of individuals being diagnosed and treated. Within the next year, all patients at the MCJ will also be offered screening for Hepatitis C, chlamydia, gonorrhea and syphilis. This may also result in more patients agreeing to be screened, and subsequently diagnosed with HIV.
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Books on the topic "Maricopy County"

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Burton, Nancy Clark. Maricopa County Sheriffs Office, Phoenix, Arizona. [Atlanta, Ga.?]: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, 1997.

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Witzeman, Janet Lauster. Birds of Phoenix and Maricopa County, Arizona. 2nd ed. Phoenix, AZ: Maricopa Audubon Society, 1997.

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Services, Arizona Department of Health. Stroke hospitalizations in Maricopa County: 1998 status report. [Phoenix]: Arizona Dept. of Health Services, 2000.

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Capesius, Joseph P. Determination of channel change for selected streams, Maricopa County, Arizona. Tucson, Ariz: U.S. Dept. of the Interior, U.S. Geological Survey, 2002.

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Capesius, Joseph P. Determination of channel change for selected streams, Maricopa County, Arizona. Tucson, Ariz: U.S. Geological Survey, Water Resources Division, 2002.

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Community Information & Referral (Phoenix, Ariz.). Directory of human services and self-help support groups, Maricopa County. Phoenix, Ariz: Community Information & Referral, 2001.

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Doorn, Peter L. Geologic and gravimetric investigations of the Carefree Basin, Maricopa County, Arizona. Tucson, AZ (845 N. Park Ave., Suite 100, Tucson 85719): Arizona Geological Survey, 1991.

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O'Day, C. M. Computed roughness coefficients for Skunk Creek above Interstate 17, Maricopa County, Arizona. Tucson, Ariz: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.

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O'Day, C. M. Computed roughness coefficients for Skunk Creek above Interstate 17, Maricopa County, Arizona. Tucson, Ariz: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.

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O'Day, C. M. Computed roughness coefficients for Skunk Creek above Interstate 17, Maricopa County, Arizona. Tucson, Ariz: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.

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Book chapters on the topic "Maricopy County"

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Goldkamp, John S., Michael R. Gottfredson, Peter R. Jones, and Doris Weiland. "The Courts in Boston, Dade County, and Maricopa County." In Personal Liberty and Community Safety, 47–68. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1821-1_4.

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Goldkamp, John S., Michael R. Gottfredson, Peter R. Jones, and Doris Weiland. "The Nature of Bail Decisionmaking in Maricopa County." In Personal Liberty and Community Safety, 93–112. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1821-1_7.

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Goldkamp, John S., Michael R. Gottfredson, Peter R. Jones, and Doris Weiland. "The Implementation of Pretrial Release Guidelines in Maricopa County." In Personal Liberty and Community Safety, 229–50. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1821-1_15.

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Lynch, Mona. "(Im)migrating Penal Excess: Sheriff Joe Arpaio and the Case of Maricopa County, Arizona." In Extreme Punishment, 68–90. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137441157_5.

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Pruetz, Rick. "Maricopa County, Arizona." In Lasting Value, 99–104. Routledge, 2017. http://dx.doi.org/10.4324/9781351179140-14.

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"Joe Arpaio, Sheriff, Maricopa County, Arizona, USA." In Trends in Policing, 173–88. 1 Edition. | New York : Routledge, [2017] | Series: Interviews: Routledge, 2016. http://dx.doi.org/10.1201/9781315390543-20.

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Peterson, Scharff. "9 Joe Arpaio, Sheriff, Maricopa County, Arizona, USA." In Trends In Policing, 139–54. CRC Press, 2016. http://dx.doi.org/10.1201/9781315390543-10.

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Fleury-Steiner, Benjamin, Paul Kaplan, and Jamie Longazel. "Racist Localisms and the Enduring Cultural Life of America’s Death Penalty: Lessons from Maricopa County, Arizona." In Studies in Law, Politics, and Society, 63–85. Emerald Group Publishing Limited, 2015. http://dx.doi.org/10.1108/s1059-433720150000066003.

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Ross, Andrew. "Viva Los Suns." In Bird on Fire. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780199828265.003.0012.

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In other Southwestern cities, like Tucson, El Paso, and Albuquerque, with Mexican urban cores that preexisted Anglo settlement, a cultural, if not political, condominium of power sharing had evolved over time. Phoenix was a more straightforward product of Anglo America. Notwithstanding that Trinidad Mejia Escalante, the wife of the founding father, Jack Swilling, was Mexican, the city’s origin myth was one of Anglos re-creating a city on top of Hohokam remnants, and it was reinforced by a strong presence of Mormon settlers in the East Valley, with their own version of white pioneerism. Anglo dominance was unquestioned for at least a century. As an early twentieth-century promoter put it, Phoenix was “a modern town of 40,000 people, and the best kind of people too. A very small percentage of Mexicans, negroes, or foreigners.” For sure, the public drama and energy of the civil rights era ushered some nonwhite politicians into high office—Raul Castro became governor and Alfredo Gutierrez senate majority leader in the late 1970s. But it was only in recent years that Anglo ascendancy had been challenged by the mercurial growth of the Latino population (according to the 2010 U.S. census, 30.8 percent of the state, 31.8 percent of Maricopa County, and 34.1 percent of Phoenix itself, all numbers that had more than doubled since 1990), spreading well beyond the traditional barrio districts where its political representatives had been contained. Anxiety about the decline of demographic and political dominance was a new wrinkle in the ongoing debate about population growth that Phoenix had long hosted. Historically, most of the anxiety about growth was founded, with good reason, on fears that water supplies would not be adequate for the rapidly expanding urban needs. Concerns about the deterioration of air quality, wilderness loss, and the overall environmental impact of urban sprawl had sharpened the anxiety over time. But the influx of Mexican immigrants from the south after the passage of NAFTA changed its tenor. Metro Phoenix had only 86,593 foreign-born residents in 1980, and by 2005, 612,850 were foreign-born, most of them from Mexico.
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Conference papers on the topic "Maricopy County"

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Sabol, George V., and Amir M. Motamedi. "Design Rainfall Criteria for Maricopa County, Arizona." In 29th Annual Water Resources Planning and Management Conference. Reston, VA: American Society of Civil Engineers, 1999. http://dx.doi.org/10.1061/40430(1999)173.

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Nelson, E. James, Christopher M. Smemoe, and Bing Zhao. "A GIS Approach to Watershed Modeling in Maricopa County, Arizona." In 29th Annual Water Resources Planning and Management Conference. Reston, VA: American Society of Civil Engineers, 1999. http://dx.doi.org/10.1061/40430(1999)155.

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Reports on the topic "Maricopy County"

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Author, Not Given. New Waddell-Westwing 230-kV transmission project, Maricopa County, Arizona: Environmental assessment. Office of Scientific and Technical Information (OSTI), October 1988. http://dx.doi.org/10.2172/6327477.

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Determination of channel change for selected streams, Maricopa County, Arizona. US Geological Survey, 2002. http://dx.doi.org/10.3133/wri014209.

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Geologic map of the Woolsey Peak Wilderness Study Area, Maricopa County, Arizona. US Geological Survey, 1989. http://dx.doi.org/10.3133/mf2044.

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Computed roughness coefficients for Skunk Creek above Interstate 17, Maricopa County, Arizona. US Geological Survey, 2000. http://dx.doi.org/10.3133/wri994248.

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Mineral resources of the Signal Mountain Wilderness Study Area, Maricopa County, Arizona. US Geological Survey, 1989. http://dx.doi.org/10.3133/b1702c.

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Mineral resources of the Woolsey Peak Wilderness Study Area, Maricopa County, Arizona. US Geological Survey, 1989. http://dx.doi.org/10.3133/b1702f.

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Mineral resources of the Sierra Estrella Wilderness Study Area, Maricopa County, Arizona. US Geological Survey, 1989. http://dx.doi.org/10.3133/b1702i.

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Mineral resources of the Big Horn Mountains Wilderness Study Area, Maricopa County, Arizona. US Geological Survey, 1987. http://dx.doi.org/10.3133/b1701a.

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Health hazard evaluation report: HETA-96-0241-2634, Maricopa County Sheriff's Office, Phoenix, Arizona. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, April 1997. http://dx.doi.org/10.26616/nioshheta9602412634.

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Potential flood hazards and hydraulic characteristics of distributary-flow areas in Maricopa County, Arizona. US Geological Survey, 1994. http://dx.doi.org/10.3133/wri934169.

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