Philosopy Assignment Example | Topics and Well Written Essays - 750 words - 1

Philosopy - Assignment Example For this reason, the Chinese Government is immoral for killing unwanted orphans. 5. This is an informal fallacy. This is because of the verbal abuse against Bachmann and it doesn’t have logic because the writer doesn’t make any sense in the statement. First, the writer writes about Bachmann’s favor in drilling the oil, then verbally abuses her. The statement Bachmann wouldn’t recognize an oil well if she bumped into one doesn’t relate to the first one. This is because everyone wants to belong to particular group and wants to feel united with a crowd, and this evokes a sense of belonging and unity. Once everyone has read this novel, then there is approval and acceptable from the crowd. This is because Senator Barrow is the first arguer; he has presented an argument on the increased social security benefits. The second arguer attacks the senator’s argument by equating it with an argument for socialism. He attacks socialism and concludes that socialism is unrealistic. Since Senator Barrow had nothing to do with socialism, this means the second arguer commits the straw man fallacy. This is because the writer’s argument ignores the Norris argument and instead, attacks his family and personal attributes that are irrelevant to whether he was responsible for the collapse of the central bank tower. Instead, the argument attacks him in a fallacious way. This is because there are two correct conclusions that are implied by the first argument. That Pearson supports the argument that evolution should be discounted and that he is a cocaine-snorting pervert and at the same time, a member of the communist party. This statement misses the point entirely. This is because the appeal uses force. If David Cole is not appointed as the new sales manager there is bound to be severe personnel cutbacks in the department. The threat imposed on the department

The Keys Stages in the Capital Investment Decision-Making Process Essay

The Keys Stages in the Capital Investment Decision-Making Process - Essay Example This research will begin with the identifying investment opportunities. Once the capital investment strategy and budgetary processes are developed, the remaining process hinges on the generation of good investment ideas.   Projects do not exist merely to be discerned, rather opportunities for investment need to be highlighted or created, and subsequently exploited.   Initial investigation of the proposal pursues highlighting the projects’ feasibility (both technically and commercially). The origination of the proposal can come either from laid mechanisms that the entity has established to scan the environment for investment opportunities; technological developments/changes; or from those working in technical positions. Investment opportunities or proposals could emanate from analysis of strategic choices, an investigation of the present business environment, research and development, or legal requirements. A two-stage decision approach can be an effective way of encouragin g investment ideas whereby, first, organizational personnel is encouraged to advance any preliminary undeveloped ideas that they have. The advanced ideas are then reviewed in the first stage and those that fail feasibility test screened out using decision criteria. The most promising ideas continue to the next stage whereby thorough financial and strategic appraisals are undertaken.   The core requisite in this stage details that investment proposal should reinforce the attainment of organizational objectives. It is essential to appreciate that even projects that fail to come to realization may produce ideas and information that benefit future investments; hence, unsuccessful projects are not merely a waste of time and effort. An investment idea cannot be evaluated until the idea has been suitably defined and presented. In reality, within the business world, capital markets are imperfect, manifested by the fact that, among other aspects, companies are usually restricted in the amo unt of finance available for capital investment. Companies, thus, need to decide between competing for investment proposals and pick those manifesting the best strategic fit and the most suitable utilization of economic resources. The company’s capital investment procedures manual should outline the requirements for project information, as well as the format of the proposal. The preferred terminology ought to be specified and defined, and the project appraisal methods and criteria should be made clear. Standardized proposal forms should allow for flexibility in the lifespan, costs, and benefits of projects. However, too much flexibility may constrain the comparability of proposals. Thus, a balance has to be struck to match the organization and the forms of projects it considers. The screening of the projects may spotlight aspects such as cash flow analysis, critical variables, documentation, and sensitivity analysis. Candidate investment proposals require an in-depth analysis and appraisal to establish projects, which avail the most attractive opportunities critical to the attainment of organizational goals such as enhancing shareholder wealth. Analysis and acceptance stage involve undertaking financial analysis of the project and comparing the project to predetermined acceptance criteria, as well as considering the project as per the capital budget for both present and future operating periods.

College Enrollment Essay Example for Free

College Enrollment Essay Income inequality has been increasing for the past 20 years. A substantial part of the increase in income differences can be explained by changes in the return to education. In dollar terms, 1973 college graduates earned 45 percent more than high school graduates; by 1994 they earned 65 percent more, based on real average hourly wages for college and high school graduates (Baumol and Blinder, 1997). The increasing income disparities between groups of differing educational attainment raises concern that access to postsecondary education (PSE) may not be as widespread as desired. President Clinton urged for the goal of universal college access in his 1997 State of the Union address, â€Å"We must make the thirteenth and fourteenth years of education—at least two years of college—just as universal in America by the 21st century as a high school education is today, and we must open the doors of college to all Americans. † Using data from the National Education Longitudinal Study of 1988 (NELS) and the National Postsecondary Student Aid Study (NPSAS), this study examines access to postsecondary education by individuals in different income and test score groups. While many studies have found a statistically significant effect of income on college enrollment,1 less attention has been paid to the effect of family income after controlling for student achievement. This study specifically addresses this issue. We also explore differences in the decision of whether or not to attend PSE or in the type of PSE attended. We are interested in whether students are substituting less expensive alternatives (such as public or 2-year institutions) for high cost institutions, or whether they are not attending PSE at all. However, we do not examine selectivity of institutions attended. Another goal of this study is to determine which factors, including high school experiences, are especially important in determining college enrollment patterns. Hossler and Maple (1993) find that information on individual background factors allows them to predict, with a high degree of accuracy, which ninth-graders will go to college. The emphasis in our study is on how 1 See, for example, Leslie and Brinkman (1987), Savoca (1990), Schwartz (1986), and Mortenson and Wu (1990). SECTION I. INTRODUCTION 1 MATHTECH, INC. early indicators, such as expectations and course-taking behavior in the eighth grade, are related to college attendance six years later. 2 Last, we explore whether financial aid availability is a critical factor in determining PSE attendance. The combined effects of shifting federal support from grants to loans, and college tuition increasing at a rate faster than inflation are expected to have a large impact on enrollment patterns for low income youth. This report examines knowledge of and attitudes toward financial aid, and the relationship between such factors and PSE attendance. We also examine the effect of financial aid receipt on PSE attendance. In summary, the main research questions addressed in this report are: 1. 2. 3. 4. What percentage of students attend PSE, and what types of PSE do they attend? How are income and test score related to who goes to college? What factors, including high school experiences, are especially important in determining college enrollment patterns? Is financial aid availability a critical factor for determining PSE attendance? The rest of the report proceeds as follows. Section II describes the literature on individual and institutional factors that affect PSE attendance. Section III provides an overview of the data used in this report. It describes the NELS data, the NPSAS data, samples and weights used in the study, and correction of standard errors for sampling techniques. Section IV examines who goes to college. The section highlights the main answers to the first two research questions posed above, in a univariate or multivariate framework. Section V examines factors related to PSE attendance. Section VI explores the importance of financial aid, including knowledge of financial aid, financial aid applications, and the relationship between being offered financial aid and PSE attendance. Last, we include a bibliography of cited references. The executive summary (at the beginning of the report) highlights our findings and provides policy implications. An NCES study, not yet released, has focused on the â€Å"pipeline to higher education† using the NELS data (NCES, 1997). SECTION I. INTRODUCTION 2 2 MATHTECH, INC. One subset of analysis for this study is the group of low income, high test score students. Low income, high test score students may have the potential to benefit greatly from PSE attendance and, therefore, we want to identify factors or constraints, particularly financial ones, that might limit the students’ educational opportunities beyond high school. SECTION I. INTRODUCTION 3 MATHTECH, INC. II. LITERATURE REVIEW Much of the research on college enrollment patterns is founded upon the â€Å"human capital† model Gary Becker advanced. According to this theory, one decides to enroll in college as an investment in future earning power. Individuals calculate the value of attending college by comparing costs (direct and indirect) with expected income gains, and they make the decision that will maximize their utility over the long term. To understand enrollment behavior according to this model, it is necessary to look at such factors as tuition levels, student financial aid, average wages for high school graduates, and the difference in lifetime earnings between high school and college graduates. Economists and others agree, however, that non-monetary factors also play a major part in the college enrollment decision. Sociologists’ models of status attainment have suggested a number of background variables that join with economic factors to influence college plans. These include both personal traits (e. g. , academic ability) and interpersonal factors, such as the level of encouragement a student receives from parents and teachers. Hossler and Maple (1993) suggest that individual decisions on enrollment can be broken down into three stages: predisposition, search, and choice. According to their research, students who will ultimately attend college can be differentiated from those who will not as early as the ninth grade. Within the econometric and sociological models outlined above, the factors affecting enrollment in college can be divided into two general types: those specific to individual students, such as academic achievement and parental education levels, and those specific to educational or vocational alternatives, such as college tuition, financial aid, and unemployment levels. Students’ enrollment decisions can be viewed as jointly determined by their individual characteristics and the institutional or societal conditions that prevail. We first review individual traits that affect college enrollment, and then institutional determinants. SECTION II. LITERATURE REVIEW 4 MATHTECH, INC. A. INDIVIDUAL FACTORS THAT AFFECT COLLEGE ENROLLMENT Several studies have used data from the National Longitudinal Study of the High School Class of 1972 (NLS72), the National Longitudinal Survey of Labor Market Experience, Youth Cohort (NLSY), and the High School and Beyond Survey (HSB) to examine the factors affecting college enrollments. Manski and Wise (1983), Rouse (1994), and a number of others have used the variables included in these data sets to estimate multinomial logit models of enrollment decisions. Among the researchers, there seems to be considerable agreement regarding the individual traits that help to determine enrollment. These traits are discussed below. Manski and Wise (1983) presented a key point, namely that the enrollment process begins with the student’s decision to apply to college. This is much more important than the decisions made by college admissions personnel, since most would-be college students are likely to be admitted to some postsecondary institution of average quality. Jackson (1988) reports that in 1972, more than 97 percent of college applicants were admitted to at least one of their top three choices. The factors of greatest interest, then, are those that cause the student to seek to enroll. Both Manski and Wise (1983) and Rouse (1994) find that individual traits such as achievement levels, high school class rank, and parental education levels are of primary importance in determining the likelihood of a student’s applying to college. They state that higher family income levels increase the probability of application as well, but to a lesser extent. Manski and Wise also cite a â€Å" ‘peer’ or high school quality effect,† such that the larger the share of a high school senior’s classmates who attend 4-year schools, the more likely he or she will be to do the same. A recent NCES report (1997) describes the relationship among six risk factors (such as changing schools two or more times) and PSE attendance rates. St. John and Noell (1989) and St. John (1990) draw similar conclusions from the NLS72 and HSB data sets. St. John and Noell state that certain â€Å"social background variables† appear to make college enrollment more likely. These include higher test scores, higher grades, higher SECTION II. LITERATURE REVIEW 5 MATHTECH, INC. maternal education levels,3 and family income, as cited by Manski and Wise and Rouse. Other key variables include participation in an academic track during high school and â€Å"high postsecondary aspirations,† as measured by students’ reporting of the highest level of schooling they expect to achieve. Hossler and Maple (1993) find that parental education levels have a stronger effect on enrollment plans than student ability or income level. Other background factors that researchers have found to be significant include the level of parental encouragement (Hossler, Braxton, and Coopersmith, 1989) and students’ own expectations about the college decision (Borus and Carpenter, 1984). Jackson (1988) concludes that test scores, grades, taking part in a college preparatory program, and attending a school with many college-going peers are the student attributes most important for college enrollment. Kohn, Manski, and Mundel (1976) report that parents’ education level has a positive effect on a student’s likelihood of enrollment, but state that this effect decreases as family income rises. A number of researchers have examined the effects of family income levels on college enrollment. Manski (1992:16) concludes that there are â€Å"persistent patterns of stratification of college enrollments by income. † Both Manski (1992) and Kane (1995) present census data for multi-year periods that show, for ascending income levels, a steadily increasing percentage of 18to 19-year-old dependent family members enrolled in college. Using the same data source, Clotfelter (1991) and Mortenson and Wu (1990) cite positive income effects for the 18- to 24year-old group as well. Hauser (1993) finds large family income effects on college enrollment for White and Hispanic families, but he finds no such effects for Black families. 3 St. John and Noell do not include paternal education levels as a variable in their study. Manski and Wise and Rouse consider maternal and paternal education levels as separate variables, but present their conclusions in terms of parental education levels as a whole. Most of the studies reviewed here do not distinguish between mother’s and father’s education levels. One exception is the study by Kohn, Manski and Mundel (1976). This study estimates a model using subsamples of the SCOPE survey from two different states. While one group shows that the father’s education level has a greater effect on the likelihood of college attendance than does the mother’s, the other group shows the mother’s education level as having a greater effect. SECTION II. LITERATURE REVIEW 6 MATHTECH, INC. B. INSTITUTIONAL FACTORS THAT AFFECT COLLEGE ENROLLMENT. In addition to the factors that operate at an individual level, researchers have found a variety of institutional factors, or factors pertaining to educational and vocational alternatives, that affect college enrollment levels. Manski and Wise (1983) include among these factors tuition level, â€Å"quality of school† (as measured by the average combined SAT score of incoming freshmen), and the availability of government and institutional financial aid. Rouse (1994) examines the factor of proximity by estimating changes in enrollments that would result from decreasing the average  distance to the nearest 2-year college. She also considers the effects of tuition levels and financial aid availability, as well unemployment rates, which serve as a measure of competing opportunities available to high school seniors. Tuition levels are another institutional factor with a significant effect on college enrollment. Leslie and Brinkman (1987) review 25 studies on this subject, and find a general consensus that a $100 increase in tuition nationwide, in 1982–1983 academic year dollars, would result in a 6 percent decline in the college participation rate for the 18- to 24-year-old group. Savoca (1990) makes the point that high tuition levels may lessen postsecondary enrollments in the aggregate by discouraging some students from ever applying to college. The effects of tuition levels are moderated in many cases by the effects of financial aid. McPherson and Schapiro (1991) state that the variable of interest should be net cost, or tuition less financial aid. At the initial stages of the enrollment decision, however, students often lack information on their eligibility for financial aid and the amount of aid they would be likely to receive. Researchers have differing views regarding the effects of financial aid on enrollment at different types of institutions. Reyes (1994) finds that increases in financial aid positively affect both 2-year and 4-year college enrollment rates, based on information from the NLSY and HSB. Manski and Wise (1983), using the NLS72, conclude that financial aid affects students’ decisions to attend 2-year institutions, as opposed to not going to college at all. However, this study finds that enrollments at 4-year schools have little sensitivity to the availability of financial aid. Manski and Wise do not consider the effect of financial aid on the student’s choice between a 2-year and a 4-year institution. SECTION II. LITERATURE REVIEW 7 MATHTECH, INC. Other researchers have compared the effects of decreasing tuition with the effects of increasing financial aid. Manski and Wise (1983) find that for those attending 2-year schools, an additional dollar of financial aid would be worth more than a one dollar reduction in tuition. St. John (1990:172) also finds that â€Å"college applicants [are] more responsive to changes in student aid than to changes in tuition,† except for those in the upper income group. Kane (1995), however, argues that while financial aid increases may be more equitable because they are means tested, they are not as effective as decreases in tuition. This is a consequence of the complexity of the financial aid application process and the unwillingness of low income families to borrow to finance a college education. When studying the effect of tuition and financial aid on PSE enrollment, the group to be especially concerned about is low income students. Leslie and Brinkman (1987) and Savoca (1990) find that tuition levels affect enrollment decisions for low income students much more than for middle and upper income groups. By the same token, the availability of financial aid is a much more crucial factor for those at lower income levels. Orfield (1992) notes that the maximum Pell grant is less than one-fifth of the tuition at an elite university. Such a gap between aid and costs, he contends, may steer many low income students toward lower cost schools. Hearn’s 1991 study supports this hypothesis. He finds that when academic ability, achievement, and other factors are controlled for, lower income students are especially likely to choose institutions of lower selectivity. Schwartz (1985) finds that low income students are affected differently by publicly provided financial aid and aid supplied by institutions. He states that public grants tend to promote greater equity among income groups in college enrollment. Private grants, however, are often awarded on the basis of academic ability, and they tend to favor students who could afford to go to college without them. Clotfelter (1991) expresses the same concern about the effects of institutional aid. Manski and Wise (1983) note that even public aid is not always awarded where the need is greatest. They state that in 1979, 59 percent of Basic Educational Opportunity Grants were awarded to students who would probably have gone to college in the absence of such aid. Table 1 summarizes the data sources used in the studies mentioned here. SECTION II. LITERATURE REVIEW 8 MATHTECH, INC. Table 1 MAIN DATA SOURCES FOR WORKS CITED IN LITERATURE REVIEW STUDY Borus, Michael E.and Carpenter, Susan A. , â€Å"Factors Associated with College Attendance of High-School Seniors† (1984) Clotfelter, Charles T. , â€Å"Demand for Undergraduate Education† (1991) Hauser, Robert M. , â€Å"Trends in College Entry among Whites, Blacks, and Hispanics† (1993) Hearn, James C. , â€Å"Academic and Nonacademic Influences on the College Destinations of 1980 High School Graduates† (1991) Hossler, Don, Braxton, John and Coopersmith, Georgia, â€Å"Understanding College Choice† (1989). Hossler, Don and Maple, Sue, â€Å"Being Undecided about Postsecondary Education† (1993) Jackson, Gregory A., â€Å"Did College Choice Change during the Seventies? † (1988) Kane, Thomas, â€Å"Rising Public College Tuition and College Entry: How Well Do Public Subsidies Promote Access to College? † (1995) Kohn, Meir G. , Manski, Charles F. , and Mundel, David S. , â€Å"An Empirical Investigation of Factors which Influence College-going Behavior† (1976) Leslie, Larry L. , and Brinkman, Paul T. , â€Å"Student Price Response in Higher Education† (1987) Manski, Charles F. , and Wise, David A. , College Choice in America (1983) Manski, Charles F. , â€Å"Income and Higher Education† (1992) McPherson, Michael S., and Schapiro, Morton Owen, â€Å"Does Student Aid Affect College Enrollment? New Evidence on a Persistent Controversy† (1991) Mortenson, Thomas G. , and Wu, Zhijun, â€Å"High School Graduation and College Participation of Young Adults by Family Income Backgrounds 1970 to 1989† (1990) National Center for Education Statistics. â€Å"Confronting the Odds: Students At Risk and the Pipeline to Higher Education† (1997). MAIN DATA SOURCES 1979 and 1980 National Longitudinal Surveys of Labor Market Experience, Youth Cohort (NLSY) Review of studies done by others, with data from Current Population Survey (CPS) and High. School and Beyond (HSB) CPS HSB, Higher Education Research Institute (HERI) data Review of studies done by others Cluster sample of 5,000 Indiana ninth graders National Longitudinal Study of the High School Class of 1972 (NLS72), HSB NLSY, HSB, CPS School to College: Opportunities for Postsecondary Education (SCOPE) Survey Meta-analysis of studies done by others NLS72 NLS72, HSB, CPS Cooperative Institutional Research Program (CIRP) data, CPS HSB, Current Population Report, CPS NELS SECTION II. LITERATURE REVIEW. 9 MATHTECH, INC. STUDY Orfield, Gary, â€Å"Money, Equity, and College Access† (1992) Reyes, Suzanne, â€Å"The College Enrollment Decision: The Role of the Guaranteed Student Loan† (1994) Rouse, Cecilia Elena, â€Å"What to Do after High School: The Two-Year versus Four-Year College Enrollment Decision† (1994) St. John, Edward P. , and Noell, Jay, â€Å"The Effects of Student Financial Aid on Access to Higher Education: An Analysis of Progress with Special Consideration of Minority Enrollment† (1989) St. John, Edward P., â€Å"Price Response in Enrollment Decisions: An Analysis of the High School and Beyond Sophomore Cohort† (1990) Savoca, Elizabeth, â€Å"Another Look at the Demand for Higher Education: Measuring the Price Sensitivity of the Decision to Apply to College† (1990) Schwartz, J. Brad, â€Å"Student Financial Aid and the College Enrollment Decision: The Effects of Public and Private Grants and Interest Subsidies† (1985) Schwartz, J. Brad, â€Å"Wealth Neutrality in Higher Education: The Effects of Student Grants† (1986) MAIN DATA SOURCES Review of history of federal student financial aid programs NLSY, HSB NLSY, HSB, CPS. NLS72, HSB HSB NLS72 HSB, CPS HSB, CPS SECTION II. LITERATURE REVIEW 10 MATHTECH, INC. III. DATA A. NELS DATA While a number of studies have used data from the National Longitudinal Survey, Youth Cohort (NLSY), the National Longitudinal Study of the High School Class of 1972 (NLS72), and the High School and Beyond Survey (HSB) to examine the factors affecting college enrollments, this work effort is among the first to use NELS to analyze these types of issues. In 1988, NELS initially surveyed over 24,000 public and private school eighth graders throughout the United States. The nationally representative eighth grade cohort was tested in four subjects (mathematics, reading, science, and social studies). Two teachers of each student (representing two of the four subjects) were also surveyed, as was an administrator from each school. On average, each of the 1,052 participating schools was represented by 24 students and five teachers. Parents were also surveyed, providing researchers with detailed information on family background variables. Since 1988, the initial eighth grade cohort has been re-surveyed three times (and has been â€Å"freshened† with new sample members). The first follow-up of NELS (spring, 1990), included the same components as the base year study, with the exception of the parent survey, which was not implemented in the 1990 round. It also included a component on early dropouts (those who left school between the end of eighth grade and the end of 10th grade). The second follow-up (spring, 1992), repeated all components of the first follow-up study and also included a parent questionnaire. However, this time only one teacher of each student (either a mathematics or a science teacher) was asked to complete a teacher questionnaire. High school transcript data were also collected for these students. A subsample of the NELS:88 second follow-up sample was again followed-up in the spring of 1994, when most sample members had been out of high school for 2 years. In all, 14,915 students were surveyed, most through computer-assisted telephone interviewing. Major content areas for the third follow-up questionnaire were: education histories; work experience histories; work-related training; family formation; opinions and other experiences; occurrence or SECTION III. DATA 11 MATHTECH, INC. non-occurrence of significant life events; and income. Data collection for this wave began on February 4, and ended on August 13, 1994. At the time the data were collected, most of the respondents were 2 years out of high school. Table 2 summarizes the components of the different waves of the surveys. Table 2 OVERVIEW OF NELS NELS Components Grades included Cohort Base Year Spring term 1988 grade 8 students: questionnaire, tests questionnaire questionnaire two teachers per student (taken from reading, mathematics, science, or social studies) First Follow-up Spring term 1990 modal grade = sophomore students, dropouts: questionnaire, tests none questionnaire two teachers per student (taken from reading, mathematics, science, or social studies) Second Follow-up Spring term 1992 modal grade = senior students, dropouts: questionnaire, tests, H. S.  transcripts questionnaire questionnaire one teacher per student (taken from mathematics or science). Third Follow-up Spring 1994 H. S. + 2 years all individuals: questionnaire none none none Parents Principals Teachers B. NPSAS DATA Because the NELS database does not contain detailed information on financial aid, the National Postsecondary Student Aid Study (NPSAS) database is used to supplement our study with additional financial aid information. This database is used to predict financial aid for the respondents in NELS based on demographic and other characteristics that are available in both databases. NPSAS is constructed specifically to provide information on financing of postsecondary education, so it is a good candidate for this use. This database surveys a nationally representative sample of undergraduate, graduate, and first-professional students attending less than 2-year, 2-year, 4-year, and doctoral granting institutions. Both students who receive and those who do not receive financial aid are surveyed. SECTION III. DATA 12 MATHTECH, INC. The 1993 NPSAS study collected information on more than 78,000 undergraduate and graduate students at about 1,100 institutions. To be eligible, students must have been enrolled between May 1, 1992 and April 30, 1993 at a postsecondary institution in the United States or Puerto Rico. The students had to be enrolled in courses for credit, and in a program of 3 months or longer. Also eligible for inclusion were students who received a bachelor’s degree between July 1, 1992 and June 30, 1993. Students who were enrolled in a GED program or who were also enrolled in high school were not included. C. SAMPLE AND WEIGHTS Of the 14,915 respondents in the third NELS follow-up, 13,120 are represented in all four waves of the NELS data. The remaining 1,795 respondents are either first follow-up â€Å"freshened† students,4 second follow-up freshened students,5 base-year ineligibles,6 or base-year eligible students who declined to participate in one or more of the survey waves, but who did participate in the third survey wave. The breakdown of these 1,795 respondents is as follows: 501 first follow-up freshened students, 102 second follow-up freshened students, 271 base-year ineligibles, and 921 base-year eligibles with missing survey waves. To take advantage of the longitudinal nature of the NELS data and to be consistent across models and issues in the report, we focus our work on the sample of 13,120 respondents represented in all four waves of the NELS data. Consequently, the weight used in our analyses, (â€Å"F3PNLWT†) applies to sample members who completed questionnaires in all four rounds of NELS:88. As a result, the longitudinal analyses that we conduct, and the estimates that are produced in this study can only be used to make projections to the population of spring 1988 eighth graders. In the descriptive tables, all percentages are weighted using F3PNLWT, including the analyses with the high school transcript data. Those who were tenth graders in 1990 but were not in the base-year sampling frame, either because they were not in the country or because they were not in the eighth grade in the spring term of 1988. Those who were 12th graders in 1992 but were not in either the base year or first follow-up sampling frames, either because they were not in the country or because they were not in the eighth (10th) grade in the spring term of 1988 (1990). 6 5 4 Students excluded in 1988 due to linguistic, mental, or physical obstacles to participation. 13 SECTION III. DATA MATHTECH, INC. This sample includes dropouts, since the purpose of this study is to examine the overall question of what characteristics of eighth graders in 1988 are related to PSE attendance. We focus on early indicators, such as educational expectations and course-taking behavior in the eighth grade, and not on the â€Å"pipeline† of high school experiences that a dropout would lack access to. However, the dropouts were not asked the same set of survey questions as the other respondents, and, therefore, some of the analysis does not include dropouts. For each of our tables or figures, we note whether or not the dropouts are included in the analysis. D. CORRECTED STANDARD ERRORS Because NELS data are collected through a multi-stage sampling scheme, calculation of standard errors through standard methods can understate these errors. The sampling technique used in NELS is a selection of schools, and then within schools, a selection of students. With this sampling method, the observations of different students may not be independent from one another. Stataâ„ ¢, the statistical software used for analysis in this report, corrects the standard errors for these sampling techniques. Except for multinomial logit models, for which this correction is not available, survey correction techniques are used, and we note whenever the corrections are not used. However, we have found that such corrections do not have a large effect on our results, and therefore, we present all results with confidence. E. VARIABLE DEFINITIONS. The appendix to this study contains definitions of the key variables used in our analysis. For each key variable, we describe how we constructed the variable and we list the names of the NELS variables used in the construction. SECTION III. DATA 14 MATHTECH, INC. IV. WHO GOES TO COLLEGE? A. WHAT PROPORTION OF STUDENTS ATTEND COLLEGE, AND WHAT TYPE OF COLLEGE DID THEY ATTEND? We begin our analysis by examining the demographics of postsecondary school choice and discussing our main findings regarding college attendance rates and types of postsecondary education (PSE) attended. As shown in Table 3, a majority of 1988 eighth graders attend some type of PSE by 1994. Overall, 62. 7 percent of the respondents attend PSE. (Note that in all of the tables in this report, all percentages are weighted. ) Students are most likely to attend a 4-year public or a less than 4-year public school. Approximately 24 percent of the students attend each of these types of schools. Next most common are 4-year private schools. Just over 11 percent of the respondents attend 4-year private schools. Only 4 percent of the respondents attend less than 4-year private schools. Thirty-seven percent of the respondents do not attend any type of PSE. Women are slightly more likely than men to attend PSE. While 60 percent of men attend PSE, 65 percent of women attend. Women are more likely than men to attend 4-year private schools and less than 4-year private schools. Native Americans, Blacks, and Hispanics are least likely to attend PSE and Asians and Pacific Islanders are most likely to attend PSE. Hispanics are most likely to attend less than 4year private schools. Students whose parents have higher education levels are much more likely to attend PSE. While only 33 percent of students whose parents have less than a high school education attend PSE, 90 percent of students whose parents have an advanced degree attend PSE. SECTION IV. WHO GOES TO COLLEGE? 15 MATHTECH, INC. Table 3 DEMOGRAPHICS OF POSTSECONDARY SCHOOL CHOICE1 No PSE 4-Year Public 4-Year Private.

Relationship Between Schistosomiasis and Hepatitis C

Relationship Between Schistosomiasis and Hepatitis C Schistosomiasis is a chronic parasitic disease in tropical and is associated with a variety of clinical syndromes that may lead to severe morbidity (Bahgat et al., 2010). Due to control program over the last decade, a decline in the prevalence of human schistosomiasis in Egypt has been reported (Barakat et al., 1998; Bahgat et al., 2010); however, the disease is still endemic in many foci (El-Sahn et al., 2002; Bahgat et al., 2010). The common used method in the diagnostic of schistosomiasis is stool examination, using the Kato-Katz method (Carvalho et al., 2011); However, this method presents limitation for the detection of positive individuals, when the intensity of infection is low; it is less effective in determining the prevalence in low endemic areas (Feldmeier and Poggensee 1993; Kongs et al., 2001; Carvalho et al., 2011). And a relatively time consuming nature of this method in application for epidemiological assessment and clinical use (Van Etten et al., 1994; Hamilton et al., 1998; Corachan , 2002; Van Dam et al., 2004). And it is difficult to detect ova in rectal biopsy specimens in chronic infections due to the intense fibrosis present around the eggs (Attallah et al., 1999). Several schistosome serodiagnostic assays designed for the detection of specific anti-schistosome (antibodies) (Doenhoff et al., 1989; Maddison, 1987; Attallah et al., 1999). Prepatent and early infections may not have stimulated a detectable antibody response and Positive tests do not necessarily denote an active (living) infection. Antibody tests are also prone to cross reactions with other infections (Strrouk, 2001). HCV is a serious public health prob ­lem affecting 170 million carriers worldwide. It is a leading cause of chronic hepatitis (Thong et al., 2014). In Egypt, the older generations have a higher HCV prevalence than younger ones. Geographically, areas near the Nile River continue to exhibit very high rates of infection (Sievert et al., 2011). Chronic HCV infection may cause liver cirrhosis and (HCC) over the course of two or more decades (lee et al., 2008), and is the primary cause for liver transplanta ­tion worldwide (Thong et al., 2014), There is no vaccine available for prevention of HCV infection due to high degree of strain variation (Ashfaq et al., 2011). A previous study by Albeldawi et al (2010) reported that the patients with risk factors for HCV infection and abnormal liver enzyme levels, HCV infection is probable but not certain. In the present study 275 serum samples were tested for anti-HCV antibodies and 205/275 only contain anti-HCV antibodies with percent (74.5%) and the remaining 70 samples (25.5 %) were negative for anti-HCV antibodies. Anti-HCV antibodies alone cannot discriminate patients who are infectious from those who have resolved the infection. The active infection confirmed by detected HCV-NS4 antigen in serum samples using ELISA according to Attallah et al., (2012) in which sensitivity and specificity of this method to detect HCV-NS4 antigen were high (90 and 96%, respectively), HCV-NS4 antigen was detected in 205( positive for anti-HCV antibodies) against 32 healthy (negative control) by using ELISA with detection rate 85.0% for CHC patient positive for anti-HCV antibodies, and 0.0% detection rate for healthy control, this mean that 174/205 only has Anti-HCV and HCV-NS4 (HCV patient) , there was extremely statistically significant between (pGhany et al (2009) reported that ALT value differs by age, race, and gender, and by body mass index, it has been suggested that the upper limit of normal (ULN) for ALT should, in fact, be 30 IU/L for men and 19 IU/L for women, but many laboratories continue to set the ULN of ALT at about 40 IU/L. In the present study, 174 HCV have high increased in transaminase enzyme as ALT, AST, and there was extremely statistically significant between (p As is customary the transaminase enzymes are biomarker of liver health. Elevated serum levels of ALT during chronic hepatitis C are associated with an increased risk of liver fibrosis progression (Hui et al., 2003; Maasoumy and Wedemeyer, 2012); lower progression rates of fibrosis were reported in patients with normal ALT levels (Mathurin et al., 1998; Maasoumy and Wedemeyer, 2012); However, there are reports of marked fibrosis (5%-30%) and even cirrhosis (1.3%) in persons with normal ALT values (Ghany et al., 2009). Normal ranges of ALP were 40-129 U/L for males and 35-104 U/L for females, ALP is elevated in a variety of diseases as bone disease, bile duct obstructed and liver disease (Bodlaj et al., 2010), and in current study ALP was elevated in CHC patient and there was statistically significant between (p0.05) platelets in CHC patients and negative control, Furthermore, T. Bilirubin was elevated in CHC patient and there was statistically significant between (p0.05) between INR-prothrombin time in CHC patient and control. A Previous study by Attallah et al (1999) reported that Schistosoma circulating antigens were used for the detection of active infection. And the detection of Schistosoma antigens was initially based on the use crude soluble egg antigens (SEA) and soluble adult worm’s protein (SWAP) (Dunne et al., 1984). And another study reported that the circulating antigens could be released from the schistosome surface or gut to the blood circulation of infected host and consequently excreted in urine (Deelder et al., 1994; Attallah et al., 1998). Several investigators have isolated and characterized many of the schistosomiasis antigens in different developmental stages of the parasite that have a potential application in immuno diagnosis (Attallah et al., 1999). And more than 100 schistosome antigens have been identified (Siddiqui et al., 2011). In The present study we aimed to detect the 63-KDa circulating antigen of Schistosoma parasites in serum samples by SDS-PAGE, immunoblotting, and ELISA technique, The antigenic target was identified by western blotting technique by using specific Mab; an intense sharp band was appeared in serum samples of infected patients with S. mansoni at 63-kDa, and no reaction with healthy sample. Consistent with these findings previously study by Attallah et al (1999) also identified a 63-kDa antigen in different extracts of Schistosoma mansoni cercariae, adult worms, and eggs and in the urine of S.mansoni-infected individuals by specific monoclonal antibody in urine patient sample. ELISA is a serological test useful for epidemiological studies, due to its high sensitivity for the diagnosis, depending on the S.mansoni antigen used in the test (Sorgho et al., 2002; Ishida et al., 2003; Alarcà ³n de Noya et al., 2007;Luo et al., 2009; Carvalho et al.,2011), and the possibility for automating the process (Carvalho et al.,2011), previous study Attallah et al (1999)used the Fast Dot-ELISA as a diagnostic tool for the detection of 63-kD circulating antigen and sensitivity of this assay was 92% among proven S. mansoni-infected individual, the specificity was 84%, PPV = 94%, and NPV = 81%. In the current study, the cutoff of 63-KDa of Schistosoma antigen was calculated, and the cutoff level = 0.33, mouse monoclonal antibody specific to S. mansoni was used as a probe in ELISA to detect 63-kDa S. mansoni antigen in serum samples from CHC patients, the 63-kDa S. mansoni antigen was detected in 118 out of total 174 chronic hepatitis C patients with detection rate (67.8%) All of the 32 controls were negative for 63-kDa S. mansoni antigen with detection rate (0.0 %) and there was extremely statistically significant between (PS.mansoni antigen in CHC patient and control. In the present study we determined the relation between 63-KDa S. mansoni antigen and laboratory parameters in the 118 serum samples from CHC patients determined, and serum ALT levels tended to increase as the level of 63-KDa antigen increased and there was extremely statistically significant between 63-KDa and ALT, serum AST levels tended to increase as the level of 63-KDa antigen increased and there was extremely statistically significant between 63- KDa and AST. Furthermore, there was negative correlation between serum albumin and 63-KDa antigen, but there was extremely statistically significant between 63-KDa and serum albumin, serum ALP levels tended to increase as the level of 63-KDa antigen increased but this was not statistically significant, total bilirubin levels tended to increase as the level of 63-KDa antigen increased but this was not statistically significant, there was negative correlation between PLTs count and 63-KDa antigen and this was not statistically significant, INR-prothrombin time levels tended to increase as the level of 63-KDa antigen increased but this was not statistically significant. Both HCV and schistosomiasis are highly endemic in Egypt and coinfection is frequently encountered (Abdel-Rahman et al., 2013). The prevalence of HCV/S.mansoni association ranged from 0.8 to 50.0% among the studies, with the highest ranges in Egypt (10 to 50%) (Van- Lume et al., 2013). A previous study by Blenton et al (2002) mentioned that Coinfections might influence disease expression. HCV has been implicated in some studies as a factor influencing the severity of schistosomiasis (Mohamed et al., 1998; Blenton et al., 2002). And, in turn, an influence of schistosomiasis on HCV severity has been suggested (Kamal et al., 2000; (Blenton et al., 2002). Another study suggests that Schistosomiasis weaken anti- HCV immune responses and worsen liver disease (Kamal et al., 2000; Kamal et al., 2001; Osada and Kanazawa, 2011). It is worthy to notice that another study by Abdel-Rahman et al (2013) reported that HCV/schistosomiasis coinfected patients have more rapid progression of hepatic fibrosis than those with HCV mono-infection encountered, the effect of such coinfection on hepatic and response to therapy remain unclear. In light of the previous by Bahgat et al (2010) real time PCR findings from, soluble egg antigen (SEA) should be considered as a potential stimulatory factor for HCV RNA that may have influenced the early detection of HCV RNA as SEA can stimulate viral replication. The higher morbidity that is observed in patients coinfected with schistosomiasis and HCV is related, at least in part, to direct stimulation of viral replication by SEA. Another study by Vanlume et al (2013) reported that when schistosomiasis and hepatitis C association is established, the clinical course develops into severe hepatocellular damage. Viral persistence and hepatic cirrhosis can develop faster than in mono-infected people. The association between schistosomiasis and hepatitis C has been studied by many investigators due to its important but, the object of current study was undertaken to determine a correlation between HCV and schistosomiasis infection in relation to evaluation of HCV-NS4 in CHC patient only and S.mansoni/HCV co-infection , from our finding r = 0.407, this means that, there was positive association was observed between 63 KD-a S. mansoni antigen and HCV-NS4 antigen, and there was extremely statistically significant between (p S. mansoni antigen and HCV-NS4 antigen, it is of interest that our study is the first to focus on the relation between 63-KDa S. mansoni antigen and HCV-NS4 antigen. In present study, we made comparison between investigated blood markers in CHC patient co-infected and HCV only, from our finding there was increase in activities of ALT, AST in CHC patients co-infected than HCV only, On the other hand, there was decrease in serum albumin level, platelets count for CHC patients co-infected compared with non-infected with S. mansoni group and there was extremely statistically significant between (pS.mansoni/HCV) co-infected and non-infected with S. mansoni (HCV only), but this was not statistically significant between ALT in CHC patients (S.mansoni/HCV) co-infected and non-infected with S. mansoni (HCV only). The transaminase enzymes are indicator of liver fibrosis, this may be that co-infection accelerate tissue damage and liver fibrosis, there was no statistically significant between ALP in CHC patients (S.mansoni/HCV) co-infected and non-infected with S. mansoni (HCV only), this was no statistically significant between bilirubin in CHC patients (S.mansoni/HCV) co-infected and non-infected with S. mansoni (HCV only), there was no statistically significant between Albumin in CHC patients (S.mansoni/HCV) co-infected and non-infected with S. mansoni (HCV only), there was no statistically significant between PLTs count in CHC patients (S.mansoni/HCV) co-infected and non-infected with S. mansoni (HCV only). In the previous study by reported that S.mansoniinfection is known to induce hepatocellular injury, which in turn, leads to the release of enzymes from the injured hepatic cells into the blood circulation (Dkhil,  2014). In current study, showed that an increase in the level of HCV-NS4 antigen in patient with S.mansoni/HCV than level of HCV-NS4 antigen in  patient with HCV only. In conclusion, the 63-KDa was the antigenic component of S.mansoni, our study showed increased activity in transaminase enzyme and decreased activity in Albumin and PLTs in S.mansoni/HCV coinfection than HCV only, and 63-KDa antigen S.mansoni has a positive correlation with HCV-NS4 antigen

Can a Firemans Ball be regarded as a documentary? :: essays research papers

Can A Fireman's Ball be regarded as a documentary? www.peacefulschoolsinternational.org/sftp/glossary.htm www.filmschools.com/glossary.html www.whitenoiseproductions.com/Glossary.htm www.dvdauthority.com "A film whose narrative is derived from non-fiction and does not feature actors" The ideas for this film came about purely by accident after Milos Forman and his co-writers had retired to the country to think of a proper follow-up film to Loves of a blonde. They decided to take the night off and go to the local Fireman's Ball and on the following evening they played cards with the firemen in this little town in the mountains. Using the time he spent with the firemen, he was able to bring a level of authenticity to the film. "Most definitions delineate documentary as a nonfiction work. Instead of filmmakers conceiving the film's subject in their imaginations, they find the basis of their works in real life and real events." "Instead of providing an outlet from the everyday world, documentary seeks to address our world and to educate us about it." Tries to inform the viewer of life under the Socialist Government. "Documentary subjects come from life, not from the imagination. The subjects chosen tend to possess some kind of cultural relevance, be it historical, social, or scientific." "The word "documentary" is rooted in the earliest, anthropological use of film to "document" or record field work. Now, it can mean everything from a classic documentation of life in a remote part of the world to a filmmaker's personal exploration of any subject under the sun." "Documentary subjects come from life, not from the imagination" "A documentary is a work in a visual or auditory medium presenting political, scientific, social, or historical subjects in a factual and informative manner." It is not a documentary in the traditional sense in that it is staged using scripts and is not outright informative. From the beginning of Milos Forman's career we see the mixture of black humour and observations of everyday life used in his films. A Fireman's Ball has the same type of humour and is based on the lives of a small community and their fire department. All of the firemen seem to be unable to perform their jobs due to their lack of competence. Apart from the fact that the firemen all seem hopeless, the prizes from the raffle keep getting stolen, the beauty pageant is a failure, the old man's house gets burnt to the ground because the firemen can't shovel snow on the flames fast enough and all he gets is the useless raffle tickets, even although this seems dull or sad it is actually quite entertaining and hilarious in some parts.

Caught in the College Conundrum?

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Leading them to Believe Essay

To serve God and our country, we must develop our talents and skills. Use what talents you possess; the wood be silent if no birds sang there except those that sang best By: Henry Van Dyke Each of possess different and unique talents that we can use to serve our country specially our God who give this special skills to us. Each of us can make a difference if we believe in ourselves that we can make it for our country because we use it on the right way // We can change other people’s life if we lead them to show their talents and not just only to hide it/ But the most important thing that we must know and not to forget is in everything that you do/ Do it all for the glory of God! Use what talents you have. Many singers, actors, dancers, philosophers, mathematicians, inventors, have succeed because they use their skills and do their best to achieve their dreams. As you can see, they use their skills to serve our country. Inventors invented many machines and technologies to make our life easy. Several singers like lea Salonga, Jessica Sanchez and Charice Pempengco have received numerous awards that brings glory on our country Philippines. Some people claim they don’t have any special talents or skills, or they don’t pursue discovering them. But God desires every member of the body of Christ to use abilities he divinely gave. Therefore, each believer has the responsibility to seek out and discover God given talents doing this can launch a lifetime of enjoyable service to God. One way to recognize our talents is to ask close friends or family members which areas they see as our strengths. In receiving this talents, we have several choices, we can set them aside in disappointment and pursue something that looks better in our own eyes, we can develop them for personal gain or we can cultivate and practice them as our own gifts back to God. When it comes to long term fulfillment, however we find greatest satisfaction when our gifts and abilities are used as intended. When God gives you a talent, he expects you to use it. It’s like a muscle, if you use it, it will grow. If you don’t, you’ll lose it. If you have a talent but are afraid to use it, or if you get lazy and don’t use it to benefit others, you’re going to lose it. Like the parable of the ten talents in the bible, if you don’t use what Godhas given you, he will take it away and give it to someone else who will. But if you use talents wisely, God will give you more. God will bless your level of faithfulness.