Microbiology BIO Essay Example | Topics and Well Written Essays - 250 words

Microbiology BIO - Essay Example This virus can only cause diseases only when the host immune system is suppressed because of diseases or medication (University of Maryland Medical Center, 2011). Most of the viruses, fungi and parasites affect the eye due to due to direct introduction. This is through surgery, trauma, transplant from infected grafts or through hermatogenous dissemination to the eye organs. The most common eye diseases are caused by fungi. The fungi yeast Candida albicans causes endogenous endophthalmitis, while the Filamentous fungi accounts to one third of all traumatic infectious keratitis. Also, the patients suffering from AIDS may contract various fungal infections of the eye because of weakened immune system (Clinical Microbiology review, 2012). The Candida spp are opportunistic type of fungal pathogens that resides within the human body. The fungal resides without people’s knowledge and causes various infections such as eye infections. When the body immune system is weakened, the fungal quickly attacks the various body parts. This fungal species has the ability to distinguish between a healthy host and unhealthy host and alter its physiology so as to tack the body (Boston,

Managing Conflict Essay Example for Free

Managing Conflict Essay Managing conflict Medicolegal issues We live in an increasingly demanding and vociferous society and incidents of conflict and aggression are sadly commonplace. Kate Taylor, Clinical Risk Manager at the Medical Protection Society offers advice on how to deal with the problem Working in general practice is busy and demanding, with increased workloads, stretched time and some patients having greater expectations of care. At times, when expectations are not met, we can find ourselves in conflict with patients and in some situations this can turn to aggression. As nurses, how should we deal with potentially difficult situations? This article aims to increase our understanding of conflict and provide strategies to deal with it effectively. It also includes practical tips to reduce risks associated with managing conflict and aggression. DEFINITIONS Conflict means different things to different people. The Health and Safety Executive defines workplace violence as any incident where staff are abused, threatened or assaulted in circumstances relating to their work, involving an explicit or implicit challenge to their safety, well-being or  health.1 Non-physical violence can be defined as the use of inappropriate words or behaviour causing distress and/or constituting harassment.'[ 2] The scale of the problem There is limited documentation relating to violence against nurses working in general practice. However, a recent survey carried out by the British Medical Association, to which 20% of doctors responded, found:[ 3] * Violence is a problem in the workplace for half of doctors (same for GPs and hospital doctors). * 1 in 3 respondents had experienced some form of violence in the workplace in the last year (same for hospital doctors and GPs). * 1 in 5 doctors reported an increase in violence in the past year, but the level remained constant for the majority. * Among doctors who reported some experience of violence, most had been the victim of verbal abuse in the past year while more than half had received a threat, and a third had been physically assaulted. Most injuries were minor, but 5% were serious. In April 2011, NHS Protect was set up. It is responsible for leading on work to protect NHS staff and resources from crime in England.[ 4] According to its statistics, physical assault against NHS staff is steadily increasing. However, these statistics do not capture the incidents where staff have been subjected to non-physical violence. In general practice, members of staff are more likely to be subjected to non-physical violence. Imagine working as a practice nurse and an unhappy patient threatens you, telling you I know where you live? We cannot underestimate the impact that such non-physical violence can have on individuals. CONTRIBUTORY FACTORS Circumstances * Members of the general practice team are particularly vulnerable as they often consult with patients alone. Doctors and practice nurses often work in small numbers. * Home visits are usually carried out alone. System and Organisational Problems * Delays, restrictions and mistakes such as lost prescriptions or delays in test results * Lack of appointments * Patient disappointment often results from unmet expectations, whether  realistic or unrealistic. Environment * Waiting room (heating, lighting, noise and seating) * Cramped consulting rooms without easy exit for health professionals * Lack of privacy * Availability of potential weapons. Patient Factors * Increased expectations and the difficulties in meeting these demands. Dissatisfaction with the care provided is perceived as the most common cause of aggression and violence * Strong patient emotions e.g. uncertainty, frustration, stress and anxiety. Anger is often secondary to emotions such as anxiety or grief * An underlying medical condition such as hypoglycaemia or psychotic illness * Physical symptoms including pain, headache or over-tiredness * Mental health problems such as * Personal problems e.g. financial, relationship, stress at work * Drugs and alcohol. Staff Factors * Under pressure staff-working in noisy cramped rooms, unable to trace or contact staff * In adequate staff numbers * Escalating the situation by confrontation, over-reacting, poor ccmmunication, inconsistencies in handling patients, patronising behaviour, ignoring a situation or falling to apologise. COMMUNICATION SKILLS Good communication with patients is likely to reduce the risk of conflict and violence. As nurses, how we communicate with our patients can have an impact on how difficult situations develop. We need to think about what we say and how we say it. We should rely on our strong communication skills to determine with our patients what they can expect from the services we provide. A study by American psychologist, Albert Mehrabian, determined that non-verbal communication represents over 50% of an interaction.[ 5] Being aware of your own body language can be the first step to understanding how it is perceived by our patients. Listening and empathising with patients are essential skills for nurses-so how do we ensure our patients know we are listening? * Give the patient your undivided attention * Dont trivialise the patients issue * How is the patient feeling are they angry, afraid, frustrated? Respond to the emotion as well as the words * Allow the patient to finish what they are saying * Ask questions, paraphrase and reflect to ensure you understand the message. CHALLENGING INTERACTIONS Challenging interactions with patients can be a significant cause of stress for nurses, yet the nature of most clinical jobs makes these encounters unavoidable. It can be difficult to communicate your point of view effectively for fear of generating conflict, which can lead to frustration and dissatisfaction, and may affect your ability to give good care. It is vital to build a trusting relationship with the patient in these circumstances; ensure you listen attentively, empathise and avoid confrontation. Maintain eye contact and try to establish a shared understanding of the patients problem. Having acknowledged their perspective, respectfully inform them of your position. Then work on achieving a mutually agreeable solution or way forward rather than focussing on points of disagreement, which can otherwise degenerate into an argument. Then help and support the patient to achieve the agreed solution. After challenging interactions that have required you to state your position, ensure there is effective communication with other members of the practice clinical team, along with a clear record of the discussions held. This will ensure consistency should the patient approach a different clinician seeking to re-negotiate an alternative plan or outcome. PRACTICAL TIPS Practices should consider: * Providing a side room or separate area to deal with upset/aggressive patients or those who need more privacy. * Providing good temperature and ventilation control, adequate seating and clear signage * Providing calming measures to reduce frustration, anxiety or boredom such as distractions in waiting room e.g. toys for children, magazines for adults * Adding an agreed marker to the summary of a patients record who has a history of violence (and ensure it is factually accurate) * Having a protocol for involving the police and removing patients from the list * Using CCTV * Ensuring all practice staff have access to panic alarms * Providing locks for all areas where patient access is restricted CONCLUSION We can and will experience conflict in general practice due to the sheer volume of patient contacts that occur every day. The key to managing a conflict situation is to try to de-escalate it as much as possible.confidentiality is central to the trust between nurses and their patients think how easy it may be to breach confidentiality when you have a situation with an aggressive patient. The Nursing and Midwifery Council Code of conduct clearly states you must respect peoples right to confidentiality.[ 6] As a last resort you can remove a patient from the practice list. However, this can be seen as an emotive issue, risking criticism from bodies such as the Parliamentary and Health Service Ombudsman, the GMC and the media. You can find useful information on how to go about it in the MPS factsheet, Removing patients from the practice list (September 2013).[ 7] http://www.medicalprotection.org/ uk/england-factsheets/removing-patients-from-the-practice-list. CASE STUDY Nurse E is about to start her clinic when she notices Mrs S on the list of patients for the day. Her heart sinks. Mrs S often presents with one or more complaints, talks nonstop and does not listen to advice provided. She knows from experience that interactions with Mrs S will be challenging. Mrs S is called in 20 minutes later than her planned appointment and she lets Nurse E know that she is not happy. Nurse E admits that her clinic is running late but tells Mrs S that she had an unavoidable emergency. She proceeds to take Mrs Ss blood pressure and other vital signs. Mrs S then asks Nurse E for a prescription for antibiotics as she is going on holiday and wants them just in case her chest flares up while away. Nurse E advises her that she will need to make an appointment to see the GP. Mrs S, now increasingly unhappy, begins to raise her voice and bang her fist on the desk, demanding a prescription before she leaves. Nurse E, staying calm, advises Mrs S that she is unable to give her a prescription as she doesnt have any active symptoms. Mrs S storms out of the consultation room pushing past Nurse E. Understandably upset, Nurse E calls the practice manager to report the incident. How could this situation have been dealt with better? * Apologise when mistakes occur or when clinics are running late. Some practices ask reception staff to inform patients when they are checking in if clinicians are behind schedule * Ensure patients are well informed about how systems at the practice work to try to reduce unrealistic expectations * Acknowledge the patients emotions and allow them to express them, which can take time. Ask the patient to tell you about their concerns. Listen actively using comments such as I see, or go on?, and nodding your head. Summarise their experiences, feelings and concerns back to them * Work with the patient to resolve the situation. Agree a plan for dealing with their concerns and moving forward. * Try to offer an alternative solution to demonstrate that you are keen to help them. For example, Im sorry Mrs S, but I am unable to give you a prescription. However, if you wish to make an appointment with one of the GPs you can discuss this with them * Consider the layout of the consulting rooms and reception area to ensure you can leave the room if the situation escalates. Aggression in healthcare settings is becoming all too common REFERENCES 1. Health and Safety Executive: work related violence www.hsegov.uk/violence 2. NHS Business Services(2012) Not part of my job http://www.nhsbsa.nhs.uk/Documents/ SecurityManagement/NP0J1 .pdf 3. British Medical Association (2008). Violence in the workplace. The experience of doctors in the UK. http://www.bma.org.uk/ap.nsf/AttachmentsByTitle/ PDFviolence08/$FILE/Violence.pdf 4. NHS Protect 2013 http://www.nhsbsa.nhs.uk/Protect.aspx 5. Mehrabian, A(1971) Silent messages Belmont, CA:Wadsworth 6. NMC(2011)The code: Standards of conduct, performance and ethics for nurses and midwives http://www.nmc-uk.org/Documents/Standards/ nmc TheCodeStandardsofConduct PerformanceAndEthicsForNursesAndMidwives%5FLargePrintVersion.PDF 7. MPS Factsheet removing patients from practices list September 2013 http://www.medicalprotection.org/uk/england-factsheets/removing-patients-from-the-practice-list ~~~~~~~~

Is globalization to be blamed for child labour

Is globalization to be blamed for child labour This paper addresses an issue that appears to be on the increase worldwide; Child Labour. Recent ILO estimates state that every seventh child in the world is engaged in working activities. Because of their familys financial difficulties these children are forced to give up their future in terms of education, health and leisure. This emphasises the importance to carry out further research and analysis on the phenomenon of child labour as well as come up with effective policy inventions in order to eliminate child labour. According to Basu (1999) designing policies should be based on careful analysis and research instead of underlying emotions or feelings towards child labour. It is extremely important to consider the precise definition of child labour before proceeding. There is immense heterogeneity in defining child labour as different groups view it differently. For example according to Ashagrie (1993) a child is categorised as labourer if the child is economically active. Then again we need to come to an agreement on what age group being a child consists of. Most studies however follow the ILOs convention No.138 and treat a person under 15 years old as a child and estimate child labour by observing economic activity of children under the age of 15. For the purpose of our study we will be looking at children between the ages 0-14. The aim of this paper is to discover the impact globalisation has had and is having on child labour. As globalization is a broad topic, I will be focusing specifically on trade liberalization, which plays an essential role within the globalization process. Liberalised trade had been the engine of capitalistic growth from colonial times; however globalization has led to a change in this pattern. Under colonialism, land conquest operated as a pre-condition and  (foreign) capital and (foreign) labour converged on land to produce goods for trade (e.g. plantation production). But, with globalization, capital is seeking investment outlets globally, where, besides marketing opportunities,  cheap labour is a key determinant. This has resulted in large scale foreign direct investment (FDI) with multi national corporations yielding the necessary structural change. LEDCs are keen to receive FDI and have gone to the extent of creating a suitable environment for such capital overlooking socia l issues.  The policy had been conducive for cheap labour in the form of children and women (e.g. garment industries within the FTZ in Sri Lanka). Economists argue that international trade is beneficial in terms of increasing the income of the country as well as creating job opportunities in the country. It is also one of the important sources of revenue for a developing country. But there is no denying that there may be losers from international trade too; for example the imports of cheap goods produced by low skilled workers may not only reduce the demand for those goods but also reduces employment opportunities for low skilled workers. Although trade can bring some disadvantages to a countrys economy, it is necessary that it does not effect the younger population who will determine the future of the economy. This paper investigates whether trade liberalization increases the incidence of child labour. Since our concern is working children, who are predominant in the developing world, my focus will be on developing countries specifically on India, Pakistan, Bangladesh, Nepal and Sri Lanka. The main reason for why it is interesting to consider these South Asian countries is due to the high proportion (40%) of the worlds child labour emerging from these countries as well as the rapid export growth monitored in these countries. One would expect a positive relationship between trade openness and child labour as more trade means more exports, which in turn means an increase in demand for labour; therefore, children enter the labour market. However this is an extremely generalised statement, the next section presents what the economic theory says about this matter. This study looks at a panel of 50 developing countries over a period of 4 decades to in order to observe the effect of trade on chil d labour. Another reason for the use of panel data is due to the fact that child labour is not a recent issue, it has been happening for several decades now, therefore it is interesting to see if there has been a trend over time. It also makes sense to observe the consequences of globalisation over time as there has been a rapid, continuous progress in information and technology which highly contributes to trade liberalization (Krugman 1995), especially in the 1980s when globalisation got in its stride. In order to test the effect of trade liberalization on child labour, a multiple regression analysis will be carried out using economic activity rate of children between 10-14 as the indicator for child labour and the countrys imports and exports (%GDP) as the measure of trade openness. In addition control variables such as GDP per capita and proportion of children between 0-14 as well as regional dummies are added to the regression. Data are mainly collected from the World Bank and UN common database. The report proceeds as follows. Chapter 2 reviews the theory of trade and how it is likely to affect child labour. The methods used to carry out the empirical analysis along with the description of the data used is described in chapter 3. The results and findings are presented in chapter 4 followed by the conclusions and possible policy recommendations in chapter 5. Theory Parents make the decisions regarding whether to send their children to school; they make these decisions by comparing benefits and costs of education as well the opportunity cost of time spent in education rather than working. Ranjan (1999) says that credit market imperfections are the reason for the existence of borrowing constraints. Therefore when parents cannot borrow against their childrens future earnings, the deep poverty forces them to send their children to work. When the country opens to trade in an unskilled labour abundant country (i.e. developing country) this may affect child labour in two ways. Firstly, the demand effect due to the increase in wage of the unskilled workers which in turn reduces the returns to skilled workers. Looking at it in this perspective makes it more likely that parents would send their children to work rather than to school. Another perspective is that households with unskilled workers become better off as they receive higher wages; therefore th ere is less of a need to send the children to work. The overall outcome will depend on which of these effects dominates (Ranjan 2001). However it is important to note that the impact of trade liberalization on child labour will be varied in different countries depending on the factor endowments of the country. Developing countries are relatively abundant in unskilled labour therefore trade growth may not have a significant impact on child labour. Krueger(1996) says that trade between two countries is determined by comparative advantage. A country has a comparative advantage in producing a good if the opportunity cost of producing that good is smaller in that country compared to other countries. The country with a comparative advantage also uses its resources most efficiently in the production of that good. So for example if developing countries specialize in goods that make use of unskilled labour, more of those goods are produced. The country gains from trade due to its specialization in the products that uses its resources more efficiently. This in turn brings more income to the country which can then be used to buy the goods and services the country desires. Domestic workers also benefit from this as the familys real income increases from producing the good the country specializes in. This theory can be linked with the two possible implications trade has on child labour as discussed by Ranjan; income effect reduces child l abour as the additional income helps parents reduce the work load of their children or the higher income to families may also mean parents would rather send their children to work. However Cigno et al (2002) found a negative relationship between trade and the incidence of child labour in their cross country study. The problems using a cross country study is that data collection methods in different countries may vary; therefore results may be less reliable when comparing. Also cross sectional  studies are carried out at one particular point in time or over a short period of time, therefore its only a snapshot. The results may be different if the study had been carried out in a different period. Findings of Shelbourne (2002) also supports the results derived from the study carried out by Cigno et al. Her reasoning was that the economy expands due to international trade which in turn increases per capita GDP reducing the need for child labourers. This is not necessarily true as an i ncrease in the volume of production within the country might mean there is higher demand for cheap labour in order to maximize profits. The Heckscher-Ohlin theory explains trade through differences in resources. For example let us now take a look at a simple framework where capital and labour are the factors of production. Under this framework a country will have comparative advantage in producing goods which intensively uses the factor with which they are abundantly endowed. According to this theory openness to trade increases demand for the good produced by the abundant factor which indirectly increases the demand for the abundant factor itself. This also increases the price of the abundant factor. In other words, countries that have a relatively high proportion of labour (labour intensive), which are mainly the developing countries will tend to export labour intensive goods and countries which are well endowed in terms of capital will export capital intensive goods. (criticize) Brown (2000) and Dixit (2000) believe that when countries involve in trade the wages are determined by the prices of the products. In conjunction with Heckscher-Ohlins model, this means the increase in price of the export products can actually reduce the incidence of child labour as adult wages rise. However according to Maskus (1997) the demand for child labour depends on the demand for export goods. In other words the higher the demand for export goods the higher the demand for child workers through higher equilibrium wages. His theory, however contradicts with Stolper Samuelsons theorem, which states that the expansion of the export sector increases adult wages and therefore it reduces the supply of child labour. These are two contradicting views as the expansion in the export sector can either increase or decrease child labour. However, all these theories are solely based on income and how child labour is affected due to the income effects triggered by trade. Perhaps other factor s such as poverty and welfare benefits should be taken in to account. It is generally accepted that liberalization under globalization has led to a maldistribution of income, which has created relative poverty. The worst affected has been the LEDCs. It is also true that certain  LEDCs, the least developed ones, are also affected by absolute poverty. When families are threatened to be  below poverty lines, child labour becomes a convenient means to enhance family incomes. Moreover part of the liberalized programme under globalization has been a reduction in welfare activities both in the developing and developed world. World Bank and IMF impose on LDCs welfare reduction as a pre-requisite for capital and any other form of assistance. It has led to privatisation in especially health and education driving a lot of families to lower income levels, eventually, culminating in denial of proper educational facilities  and the creation of child labour. Overall, the review of theory works seems to be more supportive towards a negative relationship between trade openness and child labour mainly due to the positive income effect trade brings to the country. We will now take a look at some empirical evidence to see if they support these theories. Empirical evidence The empirical evidence already found on the relationship between trade openness and child labour does not give us a clear picture. Most cross-sectional studies tend to show a negative relationship between trade improvement and the incidence of child labour. In fact in the panel study carried out by Cigno et al. (2002) there were no significant relationship between the two variables. The overall effect of trade liberalization on child labour seems to differ across countries. Kis-Katos (2007) carried out an empirical study using a panel of 91 countries measuring variables every decade from 1960-2000. However she only included the countries that reported a positive value of child labour; one needs to take into consideration that not all countries let out information about issues such as child labour and also countries tend to underreport work by children, therefore her results may have been different if these secretive countries were also included. She found an overall increase in trade openness over the decades as well as a steady decrease in the incidence of child labour. However the reliability of the data should be taken into account as illegal work or household work carried out by children may not be reported, which affect the reliability of the results. Moreover in developing countries economic censuses are rare and the ILO often makes adjustments such as intrapolating or extrapolating data in order to get estimates. This means the actual values may be over or under estimated than the true value. Cigno et al. (2002) found no empirical evidence that international trade raises child labour. In fact their cross country study shows that trade liberalisation actually decreases child labour. One of the indicators they used to measure child labour was primary school non-attendance rate. It is important to note that child not attending school does not necessarily mean the child is engaging in economic activity. It may for example be the case that the family cannot afford to send the child to school or even that the child has health problems. Therefore using primary school non attendance rate is not as appropriate as an indicator. The other indicator used was economic activity of children between ages 10-14, which clearly excludes children younger the 10 who are more of a cause of concern. However considering there are only limited data available on child labour, these indicators do give us a broad brush picture of the evolution of child labour. Issues with the reliability of data are the same as those discussed for Kis-Katoss empirical study above. As we have seen, most of the empirical findings are consistent with the theoretical considerations we discussed previously. In other words empirical work carried out so far mainly find a negative relationship between trade openness and child labour supporting most of the theories. Methodology Our empirical work is aimed at understanding whether the panel data evidence suggests a link between trade and child labour and whether there is any evidence to support our hypothesis of trade liberalization exerting an upward pressure of child labour. Data and variables In order to address the research question which is to observe whether trade liberalization increases child labour, a panel of 50 developing countries are used, where the variables are measured every ten years between 1960-2000. The focus of the regression is to observe child labour over time keeping in mind the current wave of globalisation progressed rapidly around the 1980s. However by looking at the data it is important to note that not all countries have experienced an increase in trade over each decade. There are a total of 250 observations for each variable considered over the years 1960, 1970, 1980, 1990 and 2000. A panel data method has been carried out for this analysis for several reasons. Firstly the use of panel data increases the number of observations. For example in our case using data over 5 different time periods has increased the sample size by 5 times which will help increase the precision of the regression estimates. It also increases the degrees of freedom and reduces the collinearity among explanatory variables, again increasing the precision of the estimates. Moreover it allows us to analyse important economic questions which cannot be addressed using cross sectional analysis alone. For example in our case using a cross sectional analysis will not be appropriate as we are interested in observing a trend over time. Data was taken from the World Bank development indicators (reference) and the United Nation common database. The dependent variable used is the economic activity rate of children between the ages 10-14 taken from the ILO estimates. Using this variable as an indicator for child labour has two main problems. Firstly children under the age of 10 who may be involved in child labour are excluded. Secondly this indicator does not include children working within the household, or children involved in illegal work such as prostitution. In developing countries economic censuses are rare and the ILO often makes adjustments such as intrapolating or extrapolating data in order to get estimates. This means the actual values may be over or under estimated than the true value, which also have an impact on the results. However considering the lack of data available on child labour and comparing with other indicators present, this indicator serves best available proxy for measuring child labour. As we are looking at the impact of trade on child labour the main explanatory variable used in our analysis is trade (% GDP). The trade variable gives the sum of exports and imports of goods and services measured as a share of gross domestic product. In addition to this two other control variables have been included. The control variables are GDP per capita growth (%) and the age group 0-14 as a percentage of the whole population. The reason for the use of control variables is to see if there is actually a relationship between trade and child labour given that these control variables which also affect the dependent variable are kept constant. It would have been desirable to control for variables such as poverty and differences in income distribution, but the data available was not sufficiently consistent across the countries and years we are considering. GDP per capita is used as a control variable because it controls for average income effects caused by trade liberalization. As we mentioned earlier increase in trade means countries gain new production opportunities which in turn increases GDP per capita. This positive income effect is most likely to reduce child labour. Therefore it is essential to control this variable. The other control variable used is age group 0-14 as a percentage of the whole population. This variable allows us to observe whether the increase in number of children in that given age group over the years affects child labour. The notion behind this is that the larger the families the higher the demand for income therefore a higher chance of children entering the labour force. As my main focus is on South Asian countries a regional dummy variable has been added to the regression which takes a value of 1 if the country is in South Asia and a value of 0 if not. This regional dummy helps to capture the change in child labour in the south Asian countries which is known to have a high prevalence of child labour. Results By looking at the data for every 10 years from 1960 to 2000, we can see a general increase in trade openness over time as well as a steady decrease in economic activity rates. We begin our analysis by considering the association between volume of trade (openness) and child labour for the years 1960, 1980 and 2000. This allows us to have a rough overview of how the relationship has changed (if any) before and after globalisation (considering globalisation occurred around the 1980s). 1980 This figure shows a scatter plot of the data for 1980 for the variables trade and child labour. A point on this scatter plot represents the volume of trade in 1980 and the economic activity rate of children between 10-14 in 1980 for a given country. The OLS regression line obtained by regressing these two variables is also plotted on the figure, which shows a slightly negative relationship; the estimated regression line is: CL = 26.6601794934 0.0149024702066*TRADE (1980 data) Because we have data for more than one year, we can re-examine this relation for another year. The scatter plots for the years 1960 and 2000 are given below. CL = 36.3205247048 0.119594768169*TRADE (1960 data) CL = 26.0540622351 0.109873185356*TRADE (2000 data) All three scatter plots show a negative relation between trade and child labour although year 2000 has the highest coefficient on trade implying that the reduction in child labour was greater in the year 2000 compared to 1960 and 1980. Keeping in mind that globalization took its stride in the 1980s, these scatter plots show that globalization has in fact reduced child labour further. However these plots only show what happened in that specific year, there may have been fluctuations between the years (i.e between 1980 and 1990) and also we cannot tell the trend over time using these individual plots. A better way of estimating the relationship is a regression approach that takes into account both the time and the cross section. Estimation strategy The estimation equation is of the following form: CLit = f( Tradeit, GDPit, Population 0-14it, Regional dummy for South Asiait), Where i= country x and t= time (decade t). More formally: Yit = ÃŽÂ ²1i + ÃŽÂ ²2X2it + ÃŽÂ ²3X3it + ÃŽÂ ²4X4it + ÃŽÂ ´(SAit) + ÃŽÂ µit. The anticipated signs of the coefficients: The coefficient of trade (ÃŽÂ ²2) which is what we are most interested in could either be positive or negative, although according to theory it is most likely to be negative. Coefficient of GDP (ÃŽÂ ²3) is expected to be negative as the higher the GDP per capita the lower the incidence of child labour due to the positive income effect. The coefficient of the number of children aged 0-14 (ÃŽÂ ²4) is expected to be positive as the larger the number of children per family the higher the demand for income in order to support the family. As south Asia has a high incidence of child labour, the coefficient of the dummy variable is expected to be positive and large. Dependent Variable: CL Method: Panel Least Squares Date: 03/21/10 Time: 16:24 Sample: 1 5 Periods included: 5 Cross-sections included: 50 Total panel (balanced) observations: 250 Variable Coefficient Std. Error t-Statistic Prob.  Ã‚   C -1.326061 7.182926 -0.184613 0.8537 TRADE -0.103054 0.031110 -3.312572 0.0011 GDP -0.448464 0.186588 -2.403504 0.0170 POP 0.778480 0.163337 4.766091 0.0000 SA 6.023961 3.378131 1.783223 0.0758 R-squared 0.149969   Ã‚  Ã‚  Ã‚  Mean dependent var 25.40160 Adjusted R-squared 0.136091   Ã‚  Ã‚  Ã‚  S.D. dependent var 15.99024 S.E. of regression 14.86241   Ã‚  Ã‚  Ã‚  Akaike info criterion 8.255344 Sum squared resid 54118.32   Ã‚  Ã‚  Ã‚  Schwarz criterion 8.325773 Log likelihood -1026.918   Ã‚  Ã‚  Ã‚  Hannan-Quinn criter. 8.283690 F-statistic 10.80618   Ã‚  Ã‚  Ã‚  Durbin-Watson stat 0.152585 Prob(F-statistic) 0.000000 CL = -1.32606116682 0.103053628312*TRADE 0.448464386734*GDP + 0.778479521915*POP + 6.0239606613*SA The results show the coefficients of ÃŽÂ ²2, ÃŽÂ ²3, ÃŽÂ ²4 are as expected. For a given country i, when trade liberalization varies across time by one unit, child labour decreases by 0.103 units. Similarly when GDP and population vary across time by one unit child labour decreases by 0.448 and increases by 0.778 respectively. Looking at the results it is clear that trade liberalization does not have much of an impact on child labour as indicated by a very small coefficient, which we may even interpret as there being no impact of trade on child labour. It is important to note that being a South Asian country is associated with child labour that is 6.02 units higher, everything else held constant. This was also expected as we found out earlier that a large proportion of child labour comes from South Asian countries. Our previous theory discussion implied that the relationship between openness and child labour could be either positive or negative. Our results suggest that grea ter openness is associated with slightly less child labour or even no effect on child labour. In order to test the significance of the coefficients, t-tests have been carried for each variable: Trade: H0: ÃŽÂ ²2 à ¢Ã¢â‚¬ °Ã‚ ¥ 0 (there is no relationship or a positive relationship between trade openness and child labour) H1: ÃŽÂ ²2 t = b2 = -3.313 se(b2) Under the 5% significance level the critical t-value is t(0.05,246) = -1.651. Since -3.313 GDP: H0: ÃŽÂ ²3 à ¢Ã¢â‚¬ °Ã‚ ¥ 0 (there is no relationship or a positive relationship between GDP and child labour) H1: ÃŽÂ ²3 t = b3 = -2.404 se(b3) Since -2.404 Number of children between 0-14: H0: ÃŽÂ ²4 = 0 (there is no relationship between number of children and child labour) H1: ÃŽÂ ²4 à ¢Ã¢â‚¬ °Ã‚   0 (there is a negative relationship between number of children and child labour) t = b4 = 4.77 se(b4) Since 4.77 > 1.651 we do not reject H0. In this case there is insufficient evidence in our sample to conclude that there is a relationship between number of children between 0-14 and child labour. Therefore we cannot be confident that this variable is actually has an impact on child labour. Perhaps further research into this will be useful. Estimating the regression excluding the population variable yields similar coefficients for the trade and GDP variables however the dummy variable for south Asia has a much smaller coefficient compared to when population was included. This shows that population is an important variable when considering South Asian countries and excluding it leads to an omitted variable bias especially when south Asian countries are involved. This is true as countries like India have a very large population therefore the proportion of children between 0-14 is likely to be high. As discussed earlier large number of children per household means extra income is required to support the family, which may lead to a necessity for children to work. Although population is an important variable, regressing it with child labour may not yield extremely reliable results in our case. This is because we are only taking into account children between the ages 10-14 as a measure of child labour, which is excluding the age group 0-9, whereas the population variables includes all ages between 0-14. This implies that the coefficient is likely to be much higher if we were to include economic activity rate of children between 0-14 as our dependent variable, which was not possible due to limited availability of data. This may be a reason why the coefficient of the population variable was insignificant as we found when carrying out the t-test. These results interpreted above however did not control for the characteristics of the countries. Fixed effect approach An advantage of panel data is that we are able to hold constant individual differences which allow us to focus on marginal effects of the independent variables considered. It is reasonable to into include the fixed effects model in our analysis as the data complies with the 2 basic requirements of using the fixed effects model; firstly dependent variable must be measured for each country for at least 2 periods and secondly the independent variable must change in value across the periods. There is no need to add the dummy variable in this case as the fixed effects are already controlling for location. Having the cross section as fixed yield the following results: As we can see from the table the coefficient of trade is more or less the same as before, however GDP now has a slightly positive coefficient. The regression R2 jumps from 0.0705 to 0.9097 when fixed effects are included. This shows that the country fixed effects account for a large amount of variation in the data. Although fixed effect approach has an attractive feature that allows controlling for the variables that have not or cannot be measured, they only take into account within country differences discarding any information about differences between countries. An F-test can be carried out to see if there is individual differences and it if is important to include cross section fixed effects in the model. Ho: ÃŽÂ ²11=ÃŽÂ ²12=ÃŽÂ ²13à ¢Ã¢â€š ¬Ã‚ ¦. =ÃŽÂ ²1N (no fixed effect differences) H1: the ÃŽÂ ²1i are not all equal F = (SSER SSEU) /J = 38.63 SSEU/(NT-N-(K-1)) Where the degrees of freedom J = N-1 = 50-1 = 49 and NT-N-(K-1) = (50x 5)-50-(3-1) = 198. Under the 5% significant level the critical value is Fc = 1.419 We reject Ho if F à ¢Ã¢â‚¬ °Ã‚ ¥ Fc, since 38.63 à ¢Ã¢â‚¬ °Ã‚ ¥1.419 we reject the null hypothesis of no fixed effect differences between these countries, therefore it is good to include fixed effects in the model. Overall, changes in trade over the decades had no impact or very little (decrease) effect on child labour. The other explanatory variables GDP and population also had the expected signs on the coefficients although under the fixed effects GDP had a small but positive coefficient. (what does this mean?) These finding are consistent with the theory we discussed previously. Policy interventions What can the Government do to reduce child labour? Some of the previous studies carried out on this topic have mainly mentioned improvements in schooling facilities as one of the main policy recommendations for combating child labour. For example Basu (0000) says that availability of good schools and provision of free meals for the children would be a way to reduce the number of children working. However, developing countries are generally poorer due to the lack of funds; therefore it may not be feasible to invest a lot on schooling. Moreover, attending school is only going to decrease full time work, whereas children could still be involved in part-time work after school. This shows that it is very difficult to abolish child labour completely by changes in schooling policy. Basu also mentions that a total ban on child labour may be a better option as a large scale of withdrawa

Essay --

It has become obvious that some people cannot drive without having some form of anger at other drivers. These people are usually patient and kind outside of their vehicles; but as soon as they start up their car, a strange phenomenon begins- Road rage. How can kind natured people have road rage? Is there something about driving that makes people tick? A few doctors and psychologists have found answers behind this problem, and some of the answers are quite shocking. People around other drivers have become more aggressive, territorial, and mean. It happens every day. A person could be driving the speed limit but another car behind gets frustrated, rides too closely as if they are about to crash, and then speeds past honking like a maniac. Some people who have no temper problem admit to losing control when they are driving. â€Å"For some road ragers, it’s a need for control, to counter to other drivers who they feel violate their proxemic space, or their need for possession of their lane or their part of the road. For others, it’s unchecked anger and aggression. It’s hormone-based, primitive, small-brain thinking, bringing a lack of emotional intelligence or the need to dominate someone else and their unsharable space. Add in unchecked egos, the need for superiority, narcissistic pride: my vehicle is bigger than yours.† This is quoted by Dr. Steve Albrecht who has written the article The Psychology of Road Rage. According to Dr. Steve Albrecht, it seems like some people have road rage because they feel as if they own the road, and do not let anyone get in their way. When they do, they are seen as violating the person’s space. There is also shocking news coming from Dr. Emil Coccaro, in the article ‘Road Rage’ Gets a Medical Diagnosis... ... influence emotions and actions. Another way to help with road rage would be to set a good example on the road with children so they have less of a change to have road rage problems as well. Children usually copy the way their parents are, and if they are calm on the road there is a good chance the children will too when it is their turn to drive. It seems like road rage is a mix between nature and nurture. It can be a psychological reason or how one was raised. Road rage should be more noticed than what it is today so people could do something about this growing problem. If ones who know they have a problem with road rage, they should go see a professional so they could find out why it is happening so often when it should not be; or even use the techniques mentioned before. If road rage and the dangers of it is taken more notice, a lot more lives could be saved.

History of Budweiser

In 1860, Eberhard Anheuser spearheaded the rise of the brewery that was located in St. Louis was about to flourished and was full of promise. The Anheuser family have endured the adversities of the industry and retained the popularity of their product. Budweiser is one of the world's premiere and largest purveyors of beers in the world today (Budweiser. com). It boasts of the two highest grossing beers in the world – Budweiser regular and Bud light (Budweiser.  com).Anheuser-Busch breweries was founded by a German immigrant named Adolphus Busch in 1876 and eventually adopted the name Budweiser. The name Budweiser has an evocatived feel in it and made the beer label distinct. The Busch Family was the pioneer brewery to utilize pasteurization in order to keep the freshness of the beer which fueled their success in the first years of its business.They also used the artificial refrigeration for beer and the first brewery yo use refrigerated railroad cars in order to sustain the beer's freshness and keep it chilled while being transported. Budweiser was the first brewery to bottle beer extensively for them to send it to outbound markets (Protz. 1964). Budejovicky Budvar was found in Ceske Budejovice in 1895. The beer has been brewed in Budejovice since the 14th Century in the Czechoslovakia. The German name of the Czech town Ceske Budejovice is where the name â€Å"Budweiser† originated.Budweis is where the beer was made in the Middle Ages and thus implying the place and origin of the brew. Budweiser means the beer of the Budweis area, Whereas Champaign in France describes the wine of the Champaign wineries. Logically, the Czechs claim to have the right to the name from long before the Americans even started the beer brewing (Protz. 1964). Reference Budweiser. 2007. History of Budweiser. Retrieved February 1, 2008, from Budweiser. com Protz,R. 1951. History of Beers. Encyclopedia of Beers.

Dormitory rooms Essay

As students move on in their lives after high school to college, many think that their lives will become paradise. With many house rules abandoned and without a curfew, students get the first taste of adulthood. Many think everything will be easy; however, from the dining halls to having no money students learn that being an adult is harder than parents display. Campus life shows students what they perceive is very different than the reality of life. In my opinion, living on campus in a dorm, supplies a student the full experience of the college life. When I imagined living in a dorm room, I imagined a very small room and hardly having any space to walk around. However, the rooms are actually quite big. There is plenty of room to walk around and even play some crazy, goofy games with a roommate. I thought the most exciting part of living on campus was going to be able to meet new people and live in a new environment. Because I am so far from home, my biggest hope was having a roommate who was easy to get along with and could have fun, and I definitely got that. The bathroom situation, I thought, was going to be the worst part of living on campus. However, in reality, it is not as bad as I had thought. As a student-athlete living in a dorm where the entire floor houses athletes, the bathroom has a maximum of five people using the facilities at a time. This works because of each athlete on a different schedule. In actuality, living on campus is very exciting and there should be no worry considering the problem with space, meeting new people, or the bathroom being very full to the point of not being able to use it. As an athlete living on campus at Western Nebraska Community College the athlete receives a dorm family. A dorm family is a family around town that â€Å"adopts† the student for the two years while attending the school. The family opens up their hearts and lets the athlete come into the family. The family attends sports events that the athlete plays and supports the athlete. I have a dorm family, and I love them. When I first thought of having a family that would open up their home and family to me I thought it was going to be awkward. However, having a family in town that has opened up their home and hearts has been great. It helped me know that there are people here in town who are willing to help and support me. Additionally, living in the dorms and living on their own, without parents, helps students find many new found freedoms that they did not have before. With living in the dormitories many students stay out late on all nights of the week, because they had a curfew at home and now they do not. The first week of school I stayed out late when I could. However, this staying out late situation did not last long, because I had been slammed with homework and after I was done with my homework all I wanted to do was sleep. With these newfound freedoms I learned very quickly how I was going to manage my time and make sure I got my sleep. When first living on campus I learned how easy I had it while living under my parents’ roof and the responsibilities that I didn’t have that I have now. When thinking that I was moving out of my parents’ house I thought it was going to be great. The freedoms I would have were going to be tremendous compared to what I had back home. However, when thinking of the freedoms I never thought of the responsibilities that I was going to have. When at home, laundry was done and living on campus causes me to do my own laundry and pay a dollar fifty for it. At home I always had someone harping on me to do my homework, make my bed, and clean my room, but on campus there is no one around to do that except myself. I had to learn to manage my time wisely and make sure I stayed up in my schoolwork. As a new freshman in college, like myself, sees his or her schedule and thinks, â€Å"man this is going to be a tough year. † This was my reaction when I saw mine at least. As a new student at any school I thought classes were going to be hard, one, because I didn’t know anyone; two, because I want to accomplish a difficult degree; three, because I didn’t know how I was going to manage the homework load and basketball at the same time. Although, when I got to the campus and started the school year I found out that staying caught up with school really was not as hard as many people make college seem. College classes are a lot like high school classes, just a lot more homework. Once I figured out how I could manage my time with basketball, study time, and have somewhat of a social life, my days became easier. Furthermore, expecting high quality food when entering into a college is putting a lot of confidence into the cooks that have to cook for hundreds of people everyday, three times a day. As a freshmen student entering into the college experience, I expected the food to be very good. I understood that the cooks had to cook for many people each day, but I expected that the food was going to have a lot of taste. When I first came to the campus and had my first meal the food was very good. The food on campus did not necessarily get any worse; it had gotten old. When I say old, I do not mean spoiled or rotten, I mean boring. The food all ends up tasting the same each and everyday. By the third week of living and eating on campus at the dining hall I began to realize how much I loved my mother’s home cooked meals. Lastly, money is a big problem for many college students. When I thought I was going to save all my graduation money for college, I thought that I was going to have a lot of money, but as reality turns out I have no money. Living on campus and living on my own made me realize the things I need to buy and the things I just want. The difference between what I needed and what I wanted was crucial for me to determine what I should spend my money on and what I should not. As a student-athlete I go to my parents a lot for money still, because I do have not time for a job considering homework, school, and practice time. In conclusion, campus life shows students that what they perceive is very different than the reality of life. Students living on campus have to share a dorm room with someone, the room is big, and there is not a lot of girls in the bathroom at once. Athletes have a dorm family who â€Å"adopts† them and welcomes them into their home. Students have a lot of freedom and can stay out late, but might have a lot of homework so it would be smart to not stay out. Many students also have a schedule with classes that may seem tough, but if they manage their time they will be just fine. The food is not high quality food, and it gets old. Students living on campus begin to miss the home cooked meals. Finally the money problem, I thought I was going to have a lot of money but turns out, I do not have a lot of money, I will buy what I need and not what I want.