Online Reservation For Car Service Information Technology Essay

Online Reservation For Car Service Information Technology Essay The Project of Online Reservation for Car Service is needed for the country as technology grows fast in the world. The purpose to develop this project is to provide better solution to the problems that the customers faces. This website will provide customers to reserve their car services from their home or from office. For moment, there is non- availability such reservation system in Malaysia. Customer feels hard to send their car for service, either they need to reserve using telephony system or walk in to send their car for service. At the end of these project, a prototype of justified system will develop which will provide a solution for the identify problem to improve the organizations revenue and performance. This system will be web based system where it is able to conduct an overall process of online registration and bookings too. The data will be stored in keep as privacy for each customer who has register. Finally, the proposed system will save time for the customers who have to wait the queue for those who walk in and telephone reservation. Project objective The main objective of this system is to provide customers with a much convenient and better way of booking their car services. It is an online system for car services reservation and users will have to sign up through the registration page so theyll be able to view the various car services provided by the car services centre. This way of reservation is unique in Malaysia as it has been already implemented in other countries. This system is created to manage the reservation processes through online where the previous older ways were done manually. This system would be a productive solution for users and the car services centre. It will also reduce the work process of the admin while the data will be kept securely. Project scope The scope of this online reservation for car services system covers various functions. Firstly, it covers the services information. This is when the users can view the services provided by the specified service centre. Secondly, it covers on identifying the location. Users can view on the location and images of the car services centre. This creates a better trust and understanding of the recognised service centre. Thirdly, the system covers the operating hours of the service centres. This helps the users to familiarise themselves on the operating hours of the particular centre. Fourthly, the system provides a log-in authority. This system provides access to members. This is where user who wants to send their car for services would have to register their details and car details online. Non-members can only view the basic interface of the online system. Fifthly, this system covers the frequently asked questions (FAQ). This will certainly help the users to clarify any doubts that they have regarding the car services. Sixthly, the system covers the report of the online processes. In this system, a report section where only specific authorized person are allowed to generate a report about the processes and data recorded. Seventhly, the system covers on online feedbacks. The registered user may send their feedback to the admin staff online. Finally, in order to achieve the scope of this project, various researches will be conducted through observation, questionnaire, books, journals, Internet and etc. A vast idea will be identified to complete this project to make its process go on swiftly throughout. Project deliverables The proposed system in the project will produce various plus points as being a web-based system. First is the security. This consist user/Admin login accounts, automated user ID for Admin and registered user, and a secured database. Second is a paperless work. This consists of an online record keeping which is web-based and registration can be made online at anytime and anywhere. Third is the reduction of human error. This is when the report will be generated in various forms such as PDF, Microsoft Word and Microsoft Excel which will provide a much accurate calculation. Fourth is test cases and actual testing and finally would be the documentation of this project with appropriate implementation of the system and can be made as a use manual too. Target Audience This system is targeted on car owners regardless of age, and occupation. Moreover, administrative staff in the services centre are targeted too because the proposed system will be more useful for them in the sense of reducing paper work and manual way of data keeping. Functionality of the system There are two types of functionality, which is internal functionality and External Functionality. The internal functionality are consists of administrator and the external functionality consists of user toft her system. Administration The proposed functionality of the system is to enhance a better reservation system to increase a better result in terms of accuracy of the cash flow and service management. The online reservation system will provide with Username and Password to enhance a better login security for the administrator. These is to manage the service authentication to check who has been reserved their service day by day. Therefore, the managers are able to get results to be summarized and to close the monthly transaction each every month. The accounts will be kept in a web based server to monitor and to keep track of daily operations to be determined in the future when it is necessary. User The user can register for free to use this reservation system. The login system enable user to update the current profile. Users are able to select their preferred time and date for their services. In conjunction, user able to select the pick-up and delivery service if there are interested and there are few monthly promotion can be selected. At the end of reservation, users are able to check out by selecting the payment methods. The web server will update at the back office and the management will get the updates of the particular reservation. Company Background Michelin BS Services Centre Sdn. Bhd. Source: Google Images On year 1998, Michelin has established its Representative Office while on the year 2002; Michelin Malaysia Sdn Bhd has established its headquarters in Petaling Jaya, Selangor. Currently Michelin Malaysia has made its mark in the local tyre industry. Michelin has a professional and ever growing distribution network easily recognized with a standardized store-front signage, and force strategically positioned and located at key market centres. BS Service Centre Sdn Bhd is based on Michelin sponsorship to sponsor those car centre and service centre to develop their business entire Malaysia. These service centres have 2 branches in Kuala Lumpur and another in Petaling Jaya itself. These companies will emerge more sponsorship to give opportunity to those who wants to establish their own car centre. As dated on 17 August 2012, Michelin is globally ranked 1,473,231 and ranked 11,155 in Malaysia (alexa.com). Castrol Golden Tyre Car Centre Source: Google Images Charles Cheers Wakefield established an oil company in England on the 19th March 1899. He produced a new lubricant that reform transport in the first half of the 20th century after ten years later. He named the new oil as Castrol. To this day, the name Castrol is equal to premium quality, high performance and a leading edge technology in motor oils and automotive lubricants. The headquarters for Castrol Industrial Malaysia is located in Kuala Lumpur. This company played a leading role in product technology and provides value added services to improve customers manufacturing process. Today, Castrol sponsorship has grown rapidly due to more car service centre which enables the company to give work opportunity for those are needed. One of the sponsorship companies were known as Golden Tyre Car Centre which is located in Bukit Jalil and they also have another main centre in Kota Kemunig, Shah Alam. As dated on 17 August 2012, Castrol is globally ranked 23,989,089 (alexa.com). Appendix http://www.alexa.com/siteinfo/michelin.com.my# Castrol

Investigating Special Education Internet Resources Essay

Family Village For Families of Children with Special Needs – http://www.familyvillage.wisc.edu/websites.html This website offers a wide variety of resources for the community to use when trying to navigate around the internet. It has sources such as Parent to Parent Matching, Mental health Websites, Diagnosis, and Internet resources. The Tulsa Area Alliance on Disabilities – http://208.112.118.116/disabili.html The website explains the benefits of early inclusion with students with and without disabilities. The website also breaks down the stages in which the person should be reaching milestones such as work and self-sufficiency. Tulsa Kids For Parents. For Families. For Life – http://www.tulsakids.com/October2011/Tulsa-Special-Needs-Resource-Guide/ The Tulsa Kids for Parents webstie offers five pages facilities where children with disabilities can utilize for exercise, activities, cheerleading, horseback riding and many other events that students with disabilities can participate in. This site also provides churches, foundations, learning facilities and legal services. This can be very helpful when parents are searching for activities their child may be interested or therapeutic exercise. United Way – Tulsa Area United Way – http://www.tauw.org/Member_Agencies.asp The Untied Way provides a tremendous amount of support in the Tulsa area for people with disabilities. The United Way partners with agencies to provide support for services the New Leaf that provides residential living skills classes and vocational training. Parents National Center for Learning Disabilities – http://www.ncld.org The NCLD website provides over 101 videos on different disabilities in order for parents to get an understanding of what type of disability their child may have. Not only does it provide facts about the disabilities it also provides true life stories from parents who have a child with a disability. Oklahoma Department of Human Services – http://www.okdhs.org/programsand services/dd/prvdrs/docs/providerlistab.htmlThe Department of Human Services is one of the most crucial services a parent can utilize. Having a child born with a disability is very expensive and the services the parents are offered are sometimes are life savers. Families can rely on free home visits for therapy, vouchers for formula, free shots and wellness baby checkups. Wrightslaw – http://www.wrightslaw.com/ Wrightslaw is a website that provides newsletters for parents to subscribe to concerning where to turn for Special Advocacy, Legal issues, revised regulations in education. This is a must to parents with a child that has a disability due to the fact that the website gets you headed in the right directs if a problem arises. The information is up to day on the No Child Left Behind Act. Students Funbrain – www.funbrain.com – This website provides interactive games such as connect the dots to create a picture of an animal or character. Funbrain is for all school age students and are arranged in different grade levels. KidsKnowIt Network – http://www.kidsknowit.com – The Kids Know It Network can be used as a homework helper by watching math videos on the problems a student may be struggling with. There are also bidoes on astronomy, biology, geology, history, math, memory and so much more. Teachers can utilize this website as an additional tool in the classroom. The great part about this website is it is free. Learn4Good – http://www.learn4good.com/kids/indes.htm – Learn4Good offers all ages Pre-k through 12 interactive games, lessons, math, reading, and can provide a report on student progress. At first I did not think students should be on this website but then took a closer look at what it had to offer the lower grades as well as the upper grades. Many times the older grades do not have enough educational websites to keep their interests or only geared to lower level learners. Starfall – http://www.starfall.com – Starfall offers children a large variety of learning tools to begin students learning adventures for all ages. The different categories range from learning their alphabet, colors, days, sounds to the students reading. My students with disabilities use this website when they come into the computer lab. Teachers Department of Education http://www.ed.gov The Department of Education is one of the most valuable websites that keeps teachers and administrators informed of the changing laws in education. It provides resources for grants, professional development and funding. Do2Learn http://www.do2learn.com Do2Learn is a must for teachers who teach children with autism. It allows you to print pictures of the child’s daily routine with flash cards. Self help toilet procedures, clothing, social behaviors and emotions. It offers over 2,500 pictures cards that can be printed. Most features on this site are free but there are some that you will need a subscription for. This website is a must for parents and teachers who work with Autistic students. Khan Academy http://www.khanacademy.org Khan Academy is one of the most valuable websites for teachers to utilize as a resources tool. It offers 750 math videos that allows students to view a 3-5 minute video on the math problem that they are currently working. If students struggle with a certain step of a math problem they can view the video as many times as they may need. This is great as a homework helper. Learning Disabilities Association of America http://www.ldanatl.org/aboutld/teachers/index.asp The LDA can provide a path to understanding of many of the disabilities that teachers come in contact with every day. As an educator it is important to utilize resources that can provide definitions of their student’s disabilities. It provides signs, symptoms and strategies. National Association of Special Education Teachers http://www.naset.org The NASET offers a wide range of resources for teachers such as Professional Development Courses, IEP Development Tools, E-Journals, IEP Golas, Objectives and Activities App. The most up to day features are also avail and can be utilized form your ipad or iphone app. One very important feature about this website is that it provides handouts, printable forms and reports. No Child Left Behind http://www.2.edu.gov/nclb.landing.jhtml The No Child Left Behind website offers resources for teachers and strategies that can be utilized in the classroom. Free special educational resources, bullying resources, are just some of the resources. The website also provides changes in the state standards, which is something that all teachers need to be aware of at all times.

Obesity and Fast Food Essay

January 2009 Abstract. We investigate the health consequences of changes in the supply of fast food using the exact geographical location of fast food restaurants. Specifically, we ask how the supply of fast food affects the obesity rates of 3 million school children and the weight gain of over 1 million pregnant women. We find that among 9th grade children, a fast food restaurant within a tenth of a mile of a school is associated with at least a 5. 2 percent increase in obesity rates. There is no discernable effect at . 25 miles and at . 5 miles. Among pregnant women, models with mother fixed effects indicate that a fast food restaurant within a half mile of her residence results in a 2. 5 percent increase in the probability of gaining over 20 kilos. The effect is larger, but less precisely estimated at . 1 miles. In contrast, the presence of non-fast food restaurants is uncorrelated with obesity and weight gain. Moreover, proximity to future fast food restaurants is uncorrelated with current obesity and weight gain, conditional on current proximity to fast food. The implied effects of fast-food on caloric intake are at least one order of magnitude smaller for mothers, which suggests that they are less constrained by travel costs than school children. Our results imply that policies restricting access to fast food near schools could have significant effects on obesity among school children, but similar policies restricting the availability of fast food in residential areas are unlikely to have large effects on adults. The authors thank John Cawley and participants in seminars at the NBER Summer Institute, the 2009 AEA Meetings, the ASSA 2009 Meetings, the Federal Reserve Banks of New York and Chicago, The New School, the Tinbergen Institute, the Rady School at UCSD, and Williams College for helpful comments. We thank Cecilia Machado, Emilia Simeonova, Johannes Schmeider, and Joshua Goodman for excellent research assistance. We thank Glenn Copeland of the Michigan Dept. of Community Health, Katherine Hempstead and Matthew Weinberg of the New Jersey Department of Health and Senior Services, Craig Edelman of the Pennsylvania Dept. of Health, Rachelle Moore of the Texas Dept. of State Health Services, and Gary Sammet and Joseph Shiveley of the Florida Department of Health for their help in accessing the data. The authors are solely responsible for the use that has been made of the data and for the contents of this article. 1 1. Introduction The prevalence of obesity and obesity related diseases has increased rapidly in the U. S. since the mid 1970s. At the same time, the number of fast food restaurants more than doubled over the same time period, while the number of other restaurants grew at a much slower pace according to the Census of Retail Trade (Chou, Grossman, and Saffer, 2004). In the public debate over obesity it is often assumed that the widespread availability of fast food restaurants is an important determinant of the dramatic increases in obesity rates. Policy makers in several cities have responded by restricting the availability or content of fast food, or by requiring posting of the caloric content of the meals (Mcbride, 2008; Mair et al. 2005). But the evidence linking fast food and obesity is not strong. Much of it is based on correlational studies in small data sets. In this paper we seek to identify the causal effect of increases in the supply of fast food restaurants on obesity rates. Specifically, using a detailed dataset on the exact geographical location restaurant establishments, we ask how proximity to fast food affects the obesity rates of 3 million school children and the weight gain of over 1 million pregnant women. For school children, we observe obesity rates for 9th graders in California over several years, and we are therefore able to estimate cross-sectional as well fixed effects models that control for characteristics of schools and neighborhoods. For mothers, we employ the information on weight gain during pregnancy reported in the Vital Statistics data for Michigan, New Jersey, and Texas covering fifteen years. 1 We focus on women who have at least two children so that we can follow a given woman across two pregnancies and estimate models that include mother fixed effects. The design employed in this study allows for a more precise identification of the effect of fast-food on obesity compared to the previous literature (summarized in Section 2). First, we observe information on weight for millions of individuals compared to at most tens of thousand in the standard data sets with weight information such as the NHANES and the BRFSS. This substantially increases the power of our estimates. Second, we exploit very detailed geographical location information, including distances The Vital Statistics data reports only the weight gain and not the weight at the beginning (or end) of the pregnancy. One advantage of focusing on a longitudinal measure of weight gain instead of a measure of weight in levels is that only the recent exposure to fast-food should matter. 1 2 of only one tenth of a mile. By comparing groups of individuals who are at only slightly different distances to a restaurant, we can arguably diminish the impact of unobservable differences in characteristics between the two groups. Third, we have a more precise idea of the timing of exposure than many previous studies: The 9th graders are exposed to fast food near their new school from September until the time of a spring fitness test, while weight gain during pregnancy pertains to the 9 months of pregnancy. While it is clear that fast food is generally unhealthy, it is not obvious a priori that changes in the availability of fast food should be expected to have an impact on health. On the one hand, it is possible that proximity to a fast food restaurant simply leads local consumers to substitute away from unhealthy food prepared at home or consumed in existing restaurants, without significant changes in the overall amount of unhealthy food consumed. On the other hand, proximity to a fast food restaurant could lower the monetary and non-monetary costs of accessing unhealthy food. In addition, proximity to fast food may increase consumption of unhealthy food even in the absence of any decrease in cost if individuals have self-control problems. Ultimately, the effect of changes in the supply of fast food on obesity is an empirical question. We find that among 9th grade children, the presence of a fast-food restaurant within a tenth of a mile of a school is associated with an increase of about 1. 7 percentage points in the fraction of students in a class who are obese relative to the presence at. 25 miles. This effect amounts to a 5. 2 percent increase in the incidence of obesity. Since grade 9 is the first year of high school and the fitness tests take place in the Spring, the period of fast-food exposure is approximately 30 weeks, implying an increased caloric intake of 30 to 100 calories per school-day. The effect is larger in models that include school fixed effects. Consistent with highly non–linear transportation costs, we find no discernable effect at . 25 miles and at . 5 miles. The effect is largest for Hispanic students and female students. Among pregnant women, we find that a fast food restaurant within a half mile of a residence results in 0. 19 percentage points higher probability of gaining over 20kg. This amounts to a 2. 5 percent increase in the probability of gaining over 20 kilos. The effect is larger at . 1 miles, but in contrast to the results for 9th graders, it is still discernable at . 25 miles and at . 5 miles. The increase in weight implies an increased caloric intake of 1 to 4 3 calories per day in the pregnancy period. The effect varies across races and educational levels. It is largest for African American mothers and for mothers with a high school education or less. It is zero for mothers with a college degree or an associate’s degree. Overall, our findings suggest that increases in the supply of fast food restaurants have a significant effect on obesity, at least in some groups. However, it is in principle possible that our estimates reflect unmeasured shifts in the demand for fast food. Fast food chains are likely to open new restaurants where they expect demand to be strong, and higher demand for unhealthy food is almost certainly correlated with higher risk of obesity. The presence of unobserved determinants of obesity that may be correlated with increases in the number of fast food restaurants would lead us to overestimate the role of fast food restaurants. We can not entirely rule out this possibility. However, three pieces of evidence lend some credibility to our interpretation. First, we find that observable characteristics of the schools are not associated with changes in the availability of a fast food in the immediate vicinity of a school. Furthermore, we show that within the geographical area under consideration, fast food restaurants are uniformly distributed over space. Specifically, fast food restaurants are equally likely to be located within . 1, . 25, and . 5 miles of a school. We also find that after conditioning on mother fixed effects, the observable characteristics of mothers that predict high weight gain are negatively (not positively) related to the presence of a fast-food chain, suggesting that any bias in our estimates may be downward, not upward. While these findings do not necessarily imply that changes in the supply of fast food restaurants are orthogonal to unobserved determinants of obesity, they are at least consistent with our identifying assumption. Second, while we find that proximity to a fast food restaurant is associated with increases in obesity rates and weight gains, proximity to non fast food restaurants has no discernible effect on obesity rates or weight gains. This suggests that our estimates are not just capturing increases in the local demand for restaurant establishments. Third, we find that while current proximity to a fast food restaurant affects current obesity rates, proximity to future fast food restaurants, controlling for current proximity, has no effect on current obesity rates and weight gains. Taken together, the weight of the 4 evidence is consistent with a causal effect of fast food restaurants on obesity rates among 9th graders and on weight gains among pregnant women. The results on the impact of fast-food on obesity are consistent with a model in which access to fast-foods increases obesity by lowering food prices or by tempting consumers with self-control problems. 2 Differences in travel costs between students and mothers could explain the different effects of proximity. Ninth graders have higher travel costs in the sense that they are constrained to stay near the school during the school day, and hence are more affected by fast-food restaurants that are very close to the school. For this group, proximity to fast-food has a quite sizeable effect on obesity. In contrast, for pregnant women, proximity to fast-food has a quantitatively small (albeit statistically significant) impact on weight gain. Our results suggest that a ban on fast-foods in the immediate proximity of schools could have a sizeable effect on obesity rates among affected students. However, a similar attempt to reduce access to fast food in residential neighborhoods would be unlikely to have much effect on adult consumers. The remainder of the paper is organized as follows. In Section 2 we review the existing literature. In Section 3 we describe our data sources. In Section 4, we present our econometric models and our empirical findings. Section 5 concludes. 2. Background While the main motivation for focusing on school children and pregnant women is the availability of geographically detailed data on weight measures for a very large sample, they are important groups to study in their own right. Among school aged children 6-19 rates of overweight have soared from about 5% in the early 1970s to 16% in 1999-2002 (Hedley et al. 2004). These rates are of particular concern given that children who are overweight are more likely to be overweight as adults, and are increasingly suffering from diseases associated with obesity while still in childhood (Krebs and Jacobson, 2003). At the same time, the fraction of women gaining over 60 2 Consumers with self-control problems are not as tempted by fatty foods if they first have to incur the transportation cost of walking to a fast-food restaurant. Only when a fast-food is right near the school, the temptation of the fast-food looms large. For an overview of the role of self-control in economic applications, see DellaVigna (2009). A model of cues in consumption (Laibson, 2001) has similar implications: a fast-food that is in immediate proximity from the school is more likely to trigger a cue that leads to over-consumption. 5 pounds during pregnancy doubled between 1989 and 2000 (Lin, forthcoming). Excessive weight gain during pregnancy is often associated with higher rates of hypertension, C-section, and large-for-gestational age infants, as well as with a higher incidence of later maternal obesity (Gunderson and Abrams, 2000; Rooney and Schauberger, 2002; Thorsdottir et al. , 2002; Wanjiku and Raynor, 2004). 3 Moreover, Figure 1 shows that the incidence of low APGAR scores (APGAR scores less than 8), an indicator of poor fetal health, increases sharply with weight gain above about 20 kilograms. Critics of the fast food industry point to several features that may make fast food less healthy than other types of restaurant food (Spurlock, 2004; Schlosser, 2002). These include low monetary and time costs, large portions, and high calorie density of signature menu items. Indeed, energy densities for individual food items are often so high that it would be difficult for individuals consuming them not to exceed their average recommended dietary intakes (Prentice and Jebb, 2003). Some consumers may be particularly vulnerable. In two randomized experimental trials involving 26 obese and 28 lean adolescents, Ebbeling et al. (2004) compared caloric intakes on â€Å"unlimited fast food days† and â€Å"no fast food days†. They found that obese adolescents had higher caloric intakes on the fast food days, but not on the no fast food days. The largest fast food chains are also characterized by aggressive marketing to children. One experimental study of young children 3 to 5 offered them identical pairs of foods and beverages, the only difference being that some of the foods were in McDonald’s packaging. Children were significantly more likely to choose items perceived to be from McDonald’s (Robinson et al.2007). Chou, Grossman, and Rashad (forthcoming) use data from the National Longitudinal Surveys (NLS) 1979 and 1997 cohorts to examine the effect of exposure to fast food advertising on overweight among children and adolescents. In ordinary least squares (OLS) models, they find significant effects in most specifications. 4 3 According to the Centers for Disease Control, obesity and excessive weight gain are independently associated with poor pregnancy outcomes. Recommended weight gain is lower for obese women than in others. (http://www. cdc.gov/pednss/how_to/read_a_data_table/prevalence_tables/birth_outcome. htm) 4 They also estimate instrumental variables (IV) models using the price of advertising as an instrument. However, while they find a significant â€Å"first stage†, they do not report the IV estimates because tests 6 Still, a recent review of the considerable epidemiological literature about the relationship between fast food and obesity (Rosenheck, 2008) concluded that â€Å"Findings from observational studies as yet are unable to demonstrate a causal link between fast food consumption and weight gain or obesity†. Most epidemiological studies have longitudinal designs in which large groups of participants are tracked over a period of time and changes in their body mass index (BMI) are correlated with baseline measures of fast food consumption. These studies typically find a positive link between obesity and fast food consumption. However, existing observational studies cannot rule out potential confounders such as lack of physical activity, consumption of sugary beverages, and so on. food. 5 There is also a rapidly growing economics literature on obesity, reviewed in Philipson and Posner (2008). Economic studies place varying amounts of emphasis on increased caloric consumption as a primary determinant of obesity (a trend that is consistent with the increased availability of fast food). Using data from the NLSY, Lakdawalla and Philipson (2002) conclude that about 40% of the increase in obesity from 1976 to 1994 is attributable to lower food prices (and increased consumption) while the remainder is due to reduced physical activity in market and home production. Bleich et al. (2007) examine data from several developed countries and conclude that increased caloric intake is the main contributor to obesity. Cutler et al. (2003) examine food diaries as well as time use data from the last few decades and conclude that rising obesity is linked to increased caloric intake and not to reduced energy expenditure. 6 7 Moreover, all of these studies rely on self-reported consumption of fast suggest that advertising exposure is not endogenous. They also estimate, but do not report individual fixed effects models, because these models have much larger standard errors than the ones reported. 5 A typical question is of the form â€Å"How often do you eat food from a place like McDonald’s, Kentucky Fried Chicken, Pizza Hut, Burger King or some other fast food restaurant? † 6 They suggest that the increased caloric intake is from greater frequency of snacking, and not from increased portion sizes at restaurants or fattening meals at fast food restaurants. They further suggest that technological change has lowered the time cost of food preparation which in turn has lead to more frequent consumption of food. Finally, they speculate that people with self control problems are over-consuming in response to the fall in the time cost of food preparation. Cawley (1999) discusses a similar behavioral theory of obesity as a consequence of addiction. 7 Courtemanche and Carden examine the impact on obesity of Wal-Mart and warehouse club retailers such as Sam’s club, Costco and BJ’s wholesale club which compete on price. They link store location data to individual data from the Behavioral Risk Factor Surveillance System (BRFSS. ) They find that non-grocery selling Wal-Mart stores reduce weight while non-grocery selling stores and warehouse clubs either reduce weight or have no effect. Their explanation is that reduced prices for everyday purchases expand real 7 A series of recent papers explicitly focus on fast food restaurants as potential contributors to obesity. Chou et al. (2004) estimate models combining state-level price data with individual demographic and weight data from the Behavioral Risk Factor Surveillance surveys and find a positive association between obesity and the per capita number of restaurants (fast food and others) in the state. Rashad, Grossman, and Chou (2005) present similar findings using data from the National Health and Nutrition Examination Surveys. Anderson and Butcher (2005) investigate the effect of school food policies on the BMI of adolescent students using data from the NLSY97. They assume that variation in financial pressure on schools across counties provides exogenous variation in availability of junk food in the schools. They find that a 10 percentage point increase in the probability of access to junk food at school can lead to about 1 percent increase in students’ BMI. Anderson, Butcher and Schanzenbach (2007) examine the elasticity of children’s BMI with respect to mother’s BMI and find that it has increased over time, suggesting an increased role for environmental factors in child obesity. Anderson, Butcher, and Levine (2003) find that maternal employment is related to childhood obesity, and speculate that employed mothers might spend more on fast food. Cawley and Liu (2007) use time use data and find that employed women spend less time cooking and are more likely to purchase prepared foods. The paper that is closest to ours is a recent study by Anderson and Matsa (2009) that focuses on the link between eating out and obesity using the presence of Interstate highways in rural areas as an instrument for restaurant density. Interstate highways increase restaurant density for communities adjacent to highways, reducing the travel costs of eating out for people in these communities. They find no evidence of a causal link between restaurants and obesity. Using data from the USDA, they argue that the lack of an effect is due to the presence of selection bias in restaurant patrons –people who eat out also consume more calories when they eat at home–and the fact that large portions at restaurants are offset by lower caloric intake at other times of the day. Our paper differs from Anderson and Matsa (2009) in four important dimensions, and these four differences are likely to explain the difference in our findings. incomes, enabling households to substitute away from cheap unhealthy foods to more expensive but healthier alternatives. 8 (i) First, our data allow us to distinguish between fast food restaurants and other restaurants. We can therefore estimate separately the impact of fast-foods and of other restaurants on obesity. In contrast, Anderson and Matsa do not have data on fast food restaurants and therefore focus on the effect of any restaurant on obesity. This difference turns out to be crucial, because when we estimate the effect of any restaurant on obesity using our data we also find no discernible effect on obesity. (ii) Second, we have a very large sample that allows us to identify even small effects, such as mean increases of 50 grams in the weight gain of mothers during pregnancy. Our estimates of weight gain for mothers are within the confidence interval of Anderson and Matsa’s two stage least squares estimates. Put differently, based on their sample size, our statistically significant estimates would have been considered statistically insignificant. (iii) Third, our data give us the exact location of each restaurant, school and mother. The spatial richness of our data allows us to examine the effect of fast food restaurants on obesity at a very detailed geographical level. For example, we can distinguish the effect at . 1 miles from the effect at . 25 miles. As it turns out, this feature is quite important, because the effects that we find are geographically extremely localized. For example, we find that fast food restaurant have an effect on 9th graders only for distances of . 1 miles or less. By contrast, Anderson and Matsa use a city as the level of geographical analysis. It is not surprising that at this level of aggregation the estimated effect is zero. (iv) Fourth, Anderson and Matsa’s identification strategy differs from ours, since we do not use an instrument for fast-food availability and focus instead on changes in the availability of fast-foods at very close distances. The populations under consideration are also different, and may react differently to proximity to a fast food restaurant. Anderson and Matsa focus on predominantly white rural communities, while we focus on primarily urban 9th graders and urban mothers. We document that the effects vary considerable depending on race, with blacks and Hispanics having the largest effect. Indeed, when Dunn (2008) uses an instrumental variables approach similar to the one used Anderson and Matsa based on proximity to freeways, he finds no effect for rural areas and for 9 whites in suburban areas, but strong effect for blacks and Hispanics. As we show below, we also find stronger effects for minorities. Taken together, these four differences lead us to conclude that the evidence in Anderson and Matsa is consistent with our evidence. 8 In summary, there is strong evidence of correlations between fast food consumption and obesity. It has been more difficult to demonstrate a causal role for fast food. In this paper we tap new data in an attempt to test the causal connection between fast food and obesity. 3. Data Sources and Summary Statistics Data for this project comes from three sources. (a) School Data. Data on children comes from the California public schools for the years 1999 and 2001 to 2007. The observations for 9th graders, which we focus on in this paper, represent 3. 06 million student-year observations. In the spring, California 9th graders are given a fitness assessment, the FITNESSGRAM ®. Data is reported at the class level in the form of the percentage of students who are obese, and who have acceptable levels of abdominal strength, aerobic capacity, flexibility, trunk strength, and upper body strength. Obesity is measured using actual body fat measures, which are considerably more accurate than the usual BMI measure (Cawley and Burkhauser, 2006). Data is also reported for sub-groups within the school (e. g. by race and gender) provided the cells have at least 10 students. Since grade 9 is the first year of high school and the fitness tests take place in the Spring, this impact corresponds to approximately 30 weeks of fast-food exposure. 9 This administrative data set is merged to information about schools (including the percent black, white, Hispanic, and Asian, percent immigrant, pupil/teacher ratios, fraction eligible for free lunch etc. ) from the National Center for Education Statistic’s Common Core of Data, as well as to the Start test scores for the 9th grade. The location of the school was also geocoded using ArcView. Finally, we merged in information. 8 9 See also Brennan and carpenter (2009). In very few cases, a high school is in the same location as a middle school, in which case the estimates reflect a longer-term impact of fast-food. 10 about the nearest Census block group of the school from the 2000 Census including the median earnings, percent high-school degree, percent unemployed, and percent urban. (b) Mothers Data. Data on mothers come from Vital Statistics Natality data from Michigan, New Jersey, and Texas. These data are from birth certificates, and cover all births in these states from 1989 to 2003 (from 1990 in Michigan). For these three states, we were able to gain access to confidential data including mothers names, birth dates, and addresses, which enabled us both to construct a panel data set linking births to the same mother over time, and to geocode her location (again using ArcView). The Natality data are very rich, and include information about the mother’s age, education, race and ethnicity; whether she smoked during pregnancy; the child’s gender, birth order, and gestation; whether it was a multiple birth; and maternal weight gain. We restrict the sample to singleton births and to mothers with at least two births in the sample, for a total of over 3. 5 million births. (c) Restaurant Data. Restaurant data with geo-coding information come from the National Establishment Time Series Database (Dun and Bradstreet). These data are used by all major banks, lending institutions, insurance and finance companies as the primary system for creditworthiness assessment of firms. As such, it is arguably more precise and comprehensive than yellow pages and business directories. 10 We obtained a panel of virtually all firms in Standard Industrial Classification 58 from 1990 to 2006, with names and addresses. Using this data, we constructed several different measures of â€Å"fast food† and â€Å"other restaurants,† as discussed further in Appendix 1. In this paper, the benchmark definition of fast-food restaurants includes only the top-10 fast-food chains, namely, Mc Donalds, Subway, Burger King, Taco Bell, Pizza Hut, Little Caesars, KFC, Wendy’s, Dominos Pizza, and Jack In The Box. We also show estimates using a broader definition that includes both chain restaurants and independent burger and pizza restaurants. Finally, we also measure the supply of non-fast food restaurants. The definition of â€Å"other restaurants† changes with the definition of fast food. Appendix Table 1 lists the top 10 fast food chains as well as examples of restaurants that we did not classify as fast food. The yellow pages are not intended to be a comprehensive listing of businesses – they are a paid advertisement. Companies that do not pay are not listed. 10 11 Matching. Matching was performed using information on latitude and longitude of restaurant location. Specifically, we match the schools and mother’s residence to the closest restaurants using ArcView software. For the school data, we match the results on testing for the spring of year t with restaurant availability in year t-1. For the mother data, we match the data on weight gain during pregnancy with restaurant availability in the year that overlaps the most with the pregnancy. Summary Statistics. Using the data on restaurant, school, and mother’s locations, we constructed indicators for whether there are fast food or other restaurants within . 1, . 25, and . 5 miles of either the school or the mother’s residence. Table 1a shows summary characteristics of the schools data set by distance to a fast food restaurant. Here, as in most of the paper, we use the narrow definition of fast-food, including the top-10 fast-food chains. Relatively few schools are within . 1 miles of a fast food restaurant, and the characteristics of these schools are somewhat different than those of the average California school. Only 7% of schools have a fast food restaurant within . 1 miles, while 65% of all schools have a fast food restaurant within 1/2 of a mile. 11 Schools within . 1 miles of a fast food restaurant have more Hispanic students, a slightly higher fraction of students eligible for free lunch, and lower test scores. They are also located in poorer and more urban areas. The last row indicates that schools near a fast food restaurant have a higher incidence of obese students than the average California school. Table 1b shows a similar summary of the mother data. Again, mothers who live near fast food restaurants have different characteristics than the average mother. They are younger, less educated, more likely to be black or Hispanic, and less likely to be married. 4. Empirical Analysis We begin in Section 4. 1 by describing our econometric models and our identifying assumptions. In Section 4. 2 we show the correlation between restaurant location and student characteristics for the school sample, and the correlation between The average school in our sample had 4 fast foods within 1 mile and 24 other restaurants within the same radius. 11 12 restaurant location and mother characteristics for the mother sample. Our empirical estimates for students and mothers are in Section 4. 3 and 4. 4, respectively. 13 4. 1 Econometric Specifications Our empirical specification for schools is (1) Yst = ? F1st + ? F25st + ? F50st + ? ’ N1st + ? ’ N25st + ? ’ N50st + ? Xst + ? Zst + ds + est where Yst is the fraction of students in school s in a given grade who are obese in year t; F1st is an indicator equal to 1 if there is a fast food restaurant within . 1 mile from the school in year t; F25st is an indicator equal to 1 if there is a fast food restaurant within . 25 miles from the school in year t; F50st is an indicator equal to 1 if there is a fast food restaurant within . 5 mile from the school in year t; N1st, N25st and N50st are similar indicators for the presence of non-fast food restaurants within . 1, . 25 and . 5 miles from the school; ds is a fixed effect for the school. The vectors Xst and Zst include school and neighborhood time-varying characteristics that can potentially affect obesity rates. Specifically, Xst is a vector of school-grade specific characteristics including fraction blacks, fraction native Americans, fraction Hispanic, fraction immigrants, fraction female, fraction eligible for free lunch, whether the school is qualified for Title I funding, pupil/teacher ratio, and 9th grade tests scores, as well as school-district characteristics such as fraction immigrants, fraction of non-English speaking students (LEP/ELL), share of IEP students. Zst is a vector of characteristics of the Census block closest to the school including median income, median earnings, average household size, median rent, median housing value, percent white, percent black, percent Asian, percent.

Ethical Influences and Misconduct in the Prison System - Free Essay Example

Sample details Pages: 8 Words: 2425 Downloads: 9 Date added: 2017/06/26 Category Law Essay Type Narrative essay Did you like this example? Misconduct by Prison/Correctional Officer Are ethical influences imperative in the deterring of corruption by correctional officers within the prison system? à ¢Ã¢â€š ¬Ã…“Sometimes corruption is slowed by shedding light into what was previously shadowedà ¢Ã¢â€š ¬Ã‚ . (P Wolfowitz et al 1943) The human resources in the criminal justice system, incessantly has opportunities and temptations of committing unethical acts. Inclusively in correctional institutions, correctional officers are no exception. Prisons are by nature dangerous institutions whereby correctional officers portray themselves as the last line of defense and protectors of society when all else fails. The police arrest the offenders, the judges and magistrates convicts and sentence offenders and the prison officers keeps them locked away, under lock and key; subsequently keeping the most difficult, violent, sadistic criminals away from the innocent vulnerable members of society. It could be even debated that correctional officers duties can be considered under the teleological ethical system pertaining to the bad act of physically depriving human beings of their liberty, for the good of protecting society. The prison environment is shrouded by a level of secrecy and has its own culture and level of consciousness, which incorporates the invasion of corruption. There is an assumption that prison corruption can be deterred by the promoting of certain ethical systems, such as the ethics of care, the ethics of virtue while incorporating professional ethics, all with the aim of instilling a higher level of civility to evolve the correctional system with an aim to being less corrupted and a more utilitarian success. Defining civility and corruption Civility can be described as being self aware, having good faith, fairness, equity, humility, unselfishness, generosity, transcendence, compassion, and, human sensitivity regardless of their legal liberty status or who the inmate is. (Sam S. Souryal )These characteristics transcend proponents of ethics of virtue and care. In the correctional institutions ethics of care incorporates treating others with dignity, having a sense of mindfulness and promoting a rehabilitative environment. In the ethics of virtue treating others with respect and having positive characteristics is of great significance. (Pollock J et al) Although it may be challenging at times, it is at that moment when the professional ethics comes or should come to the forefront. In contrast corruption can be characterized by the vices of dishonesty, illegality, cruelty, and often deceitfulness. Corruption reinforces the instinctive urges to fabricate, violate, illegally acquire and cover up wrong doing or unethical and corrupted acts. There are three categories of corruption. Acts of misfeasance pertains to failure to perform legitimate acts that prison officials are supposed commit but instead willingly violate for personal gain. Acts o f Misfeasance usually occurs in high ranking officials in the prison hierarchy. Acts of malfeasance pertains to the commission of illegal acts or acts of misconduct that officers knowingly commit in violation of laws and or rules and regulations, such as the improper use of authority. Acts of malfeasance are usually committed by the lower or middle management levels(Braswell, McCarthy, McCarthy, 1984, p. 235).Acts of nonfeasance pertains to failure to perform legal duty, which can occur at all level of staff within the institution. (Braswell et al., 1984, p. 234). Braswell et al. (1984, p. 234) à ¢Ã¢â€š ¬Ã…“All institutions are prone to corruption and to the vices of their members.à ¢Ã¢â€š ¬Ã‚ (Morris West et al 1916) Correctional Officers Subculture In correctional institutions there exist a correctional officers subculture. It can be argued that the beliefs, values and behaviours that form an à ¢Ã¢â€š ¬Ã…“officer codeà ¢Ã¢â€š ¬Ã‚  contributes to the rationalizati on of unethical and even illegal behaviours of correctional officers. The prison officer subculture depicts that the inmate may be considered the enemy, along with superiors and society in general. ( Sam s Souryal et al) The subculture is usually initiated and instilled on new officers by the veteran officers, often through Albert Banduraà ¢Ã¢â€š ¬Ã¢â€ž ¢s Social Learning Theory process. Whereby, an observerà ¢Ã¢â€š ¬Ã¢â€ž ¢s behaviour changes after viewing the behaviour of a model. The observer will imitate the modelà ¢Ã¢â€š ¬Ã¢â€ž ¢s behaviour if the model possesses characteristics that are desirable or acceptable. ( ) The subculture consists of, unwritten rules such as à ¢Ã¢â€š ¬Ã…“donà ¢Ã¢â€š ¬Ã¢â€ž ¢t ratà ¢Ã¢â€š ¬Ã‚ . Never rat out an officer in favour of an inmate, and never cooperate in an investigation or testify against a fellow officer in regard to that officerà ¢Ã¢â€š ¬Ã¢â€ž ¢s treatment of inmates. Never make a fellow officer look bad in front of inmates regar dless of what the officer did. Always support an officer in a dispute with an inmate, therefore donà ¢Ã¢â€š ¬Ã¢â€ž ¢t criticize a fellow officer, but instead support him or her against any inmate. Always support sanctions against inmates which include the use of illegal force. In addition dont be a white rat, meaning the prohibition of any behaviour, attitude or expressed opinion that could be interpreted as sympathetic toward inmates. Additionally there is also the perception by prison officers that they are despised by society at large and therefore should maintain officer solidarity against all outside groups, which include the media, and the general public. As a consequence of this prison officer subculture, it can be argued that the prison officer subculture contributes and maintains and supports the tremendous amount of employee unethical misconduct and corruption which is usually unreported. (. ) There exist a psychological theory developed by John Locke (. )that proposes t hat everyone is born with a blank slate also known as Tabula Rasa. Furthermore it could be envisioned that coming into the prison environment as a recruit you are being born with a blank slate and you gain your knowledge from your environment and experiences. One does not born corrupt therefore one learns corruption from associations within the job. Therefore it could be assumed that a more ethical civil work environment and ethical work culture would lower the probability of officers becoming corrupt. Rules That Guide The Trinidad and Tobago Prisons Officer Against Corrupted Practices Public agencies including correctional institutions are mandated and expected to operate within a set of rules and regulations. Some examples of the rules and regulations in the Trinidad and Tobago prison service regulations code of conduct that exist to define what is considered unethical acts or corruption, or what acts can lead to corruption, includes ; (20-e) making False Statements, that is t o say, if an officer knowingly makes a false, misleading or inaccurate statement, either orally or in any official document, or with intent to deceive, destroys or mutilates and such document or book or alters or erases any entry . False statements usually lead to a cover up of some sort. (20-h)Improper relations with prisoners or exprisoners, that is to say if a prison officer communicates with a prisoner for an improper purpose, or allows any undue familiarity between a prisoner and himself and any servant of the prisoner or knowingly and without authority communicates with any ex-prisoner; Or knowingly, and without proper authority allows any person to communicate with a prisoner who is not authorized to do so. An officer having improper relations with a inmate will only escalate to more corruption , even if being compensated for allowing unauthorized or improper communication and relations to take place. (20-j)Trafficking, that is to say if a prison officer knowingly and witho ut proper authority carries out any pecuniary or business transactions with or on behalf of any prisoner or exprisoner or with a friend or relative of any prisoner or exprisoner, or brings into the prison or carries out of the prison or attempts to carry out, to or for any prisoner any article whatever; or accepts any present or consideration from any prisoner or exprisoner or from a friend or relative of any prisoner or ex-prisoner. Trafficking mainly depicts when officers bring in or allow to be brought in dangerous contraband such as drugs, weapons, alcohol and even cell phones. (20-k)Corrupt practice, that is to say if knowingly, he solicits or receives an unauthorized fee, gratuity or other consideration in connection with his duties as a prison officer, or improperly uses his position as a prison officer for his private advantage. Unlawful or unnecessary use of authority, that is to say, if he deliberately acts in a manner calculated to provoke a prisoner, or in dealing with a prisoner uses force unnecessarily or where the application of force to a prisoner is necessary uses undue force. It has been perceived the prison officers engage in brutality against inmates. (20-d) Neglect of duty, that is if he neglects or without good and sufficient cause to promptly and diligently to do anything which it is his duty as a prison officer to do, contributes to the occurrence of any loss, damage, or injury to any person or property. It has been alleged that prison officers by turning a blind eye has allowed the physical and even sexual assault on inmates by other inmates for payment or payback for an inconceivable crime such as raping and killing of a baby or a child. Allowing a sort of jail justice. There exist a psychological theory developed by John Locke (. )that proposes that everyone is born with a blank slate also known as Tabula Rasa. Furthermore It could be envisioned that coming into the prison environment as a recruit you are being born with a blank s late and you gain your knowledge from your environment and experiences. One does not born corrupt therefore one learn corruption from associations within the job. Therefore it could be assumed that a more ethical civil work environment and ethical work culture would lower the probability of officers becoming corrupt. Correctional officers have had their careers ended in disgrace as a consequence of unethical acts which are sometimes considered illegal. Some officers may engage in brutality against an inmate or allow inmates to assault each other which could possibly result in death. Additionally officers bring in or allow to be brought in dangerous contraband such as drugs, weapons, alcohol and even cell phones. In addition, there have been accusations of officers allowing or contributing to being perpetrators of inappropriate sexual activity with inmates. Correctional officers who engage in unethical and unprofessional activities can have criminal prosecutions brought against t hem and furthermore expose the correctional institution and by extension the state to lawsuits. .( prison officers may think they are doing a good by dealing with the scome of society and by keeping society safe) if the correctional controlling authority (its leadership) is keen on promoting organizational civility, the rates of corruption by both correctional officers and inmates will fall by themselves.( VIRTUE OF CARE CAN ASSIST IN THE REDUCTION OF CORRUPTUION WITHIN THE PRISON SYSTEM) utilitarian approach, Professionalism inspires workers to excel in whatever they do, truth over deception, and social utility over personal gain-Concomitantly if a conflict arises between matters of fact and matters of value, (DISCONNANCE) professional agencies should pursue the former without ignoring the morality of the latter (simon, 1997,Souryal,2007) Civility Is Instrumental In A Positive Ethical Culture In can be contended that an ethical work environment is instrumental in th e development of an affirmative ethical work culture and with it civility and integrity. The correctional institutions must establish and implement a reformed level of ethical culture with assurance that each officer would have the knowledge of moral principles needed and expected in their performance of their job. Characteristics of ethical professionalism such as honesty, obligation, duty, responsibility and importantly the responsibility of an officer to report the administration when there is probable cause that corruption or any unethical behavior is occurring .Additionally the pillars of civility within the institution stands on the institutions inclination to act in an manner of morality rather than deceptively. Challenges in the implementation of a civil and ethical correctional organization. There exists the contention relating to the implementation of a civil and uncorrupted work force due to the optional management styles of the operational management department. The management of an institution is reinforced and sustained by its workers and in this case the officers. If the managers have adapted an egotistic managerial model of only being concerned of making they look good, it would negatively impact upon the embarkment and embracement of a civil and corrupt free organization. Additionally managers of an institution must be exemplars in the aspects of integrity and ethics. It would be hypocritical and contradictory to demand integrity and ethical behavior from the subordinate correction officers when it is being observed that the managers are using their authority to perform corrupt practices such as violating policies and using the prison resources for their own personal benefit. Also there is a managerial norm in institutions of favoritism between staff which is a factor which is sometimes used in certain aspects of the operational responsibilities and running of the institution. This managerial norm is also very detrimental to the instituti on because it promotes a negative organization culture and thereby a negative civility status. Implementing Anti-corruption Strategies There are various measures that can be implemented in the fight against corruption. A front door method is improving recruitment evaluations and requirements. The recruit stage is the ideal place and situation to improve and sustain the institutionà ¢Ã¢â€š ¬Ã¢â€ž ¢s ethical status level. The recruitment drive should incorporate psychological and character assessments for example recognition and production tests which require an applicant to reason through a dilemma and provide some rationale.(Pollock JM 2010) Managers of Correctional Institutions should ensure that their recruitment standards are at a certain level to prevent unwanted applicants from entering the service. The management group of a prison institution is very influential in its capacity in its attempt to reduce corruption. The management group must be perceived as credible thereby portraying the ethics of professionalism. They must also display the ethics of care and virtue by being consistent, reasonable, and sympathetic to the needs of both their officers and their charges. Additionally there should be a reformation of supervisory techniques. Old supervisory methods should be reformed to civil quality based techniques. Techniques such as not only involve monitoring for unethical and corrupt behavior among the subordinates but also, their colleagues. Keeping in mind the utilitarian aspect, which is supposed to surpass individual loyalty. (. ) The institutionà ¢Ã¢â€š ¬Ã¢â€ž ¢s level of civility can be measured by the cumulative talent the wors culturally gain from their work experience, REFERENCES Morris West. (n.d.). BrainyQuote.com. Retrieved March 16, 2014, from BrainyQuote.com Web site: https://www.brainyquote.com/quotes/authors/m/morris_west.html Paul Wolfowitz. (n.d.). BrainyQuote.com. Retrieved March 16, 2014, from BrainyQuote.com Web site : https://www.brainyquote.com/quotes/authors/p/paul_wolfowitz.html Deterring Corruption by Prison Personnel A Principle-Based Perspective Sam S. Souryal Sam Houston State University, Huntsville, Texas The Prison Journal Volume 89 Number 1 March 2009 21-45  © 2009 SAGE Publications Don’t waste time! Our writers will create an original "Ethical Influences and Misconduct in the Prison System" essay for you Create order