Diagnostic Assessment Essay Example for Free

Diagnostic Assessment Essay Luis is a 32-year-old male who immigrated to the U.S. when he was 14. He later became a US citizen. Although, Spanish is his native language, he speaks English extremely well. He recently returned to living with his parents after being laid off from being a semi-skilled auto worker 6 months ago. Luis is the middle of three children. He has a younger sister and older brother, his brother is away at college. Just prior to being laid off, he became involved with a young woman he claims is â€Å"the woman I’m going to marry. † He lives with his parents after being laid-off 6 months ago when he was living with friends. He was able to find a job where he works as a pizza delivery person. His mother was diagnosed with depression following the family’s move from Puerto Rico. Luis completed high school and one year of vocational training. Luis is self-referral and has concerns about his anger and impulsivity. These issues have surfaced since his returning home. Luis also wanted to know why he isn’t himself anymore. Luis stated that, â€Å"I just don’t feel like I am doing well but I don’t know why†. He reported feeling that there is really nothing bad going on in his life, yet he just feels like everything is bad. He reports that his parents are on his case because he don’t do anything other than sit around the house. His parents tell him that he needs to get himself under control. He feels like he really is not motivated to do things anymore. Luis reports that his home life finds him being harsh to his parents, especially when they make a request of him and he becomes angry over little issues. This is the same pattern he had growing up with them. He left home when he was 22-year-old to live with buddies. He frequently argues with his girlfriend. His parents attend Christian church weekly; yet, Luis only goes on some of the major holidays like Christmas and Easter. Luis reported that he was a â€Å"C† student in high school and received a certificate for skilled machinist. Luis reported that he was an okay school student but had a hard time adjusting when he first started in the States. He stated he likes what he works at and has been successful there as people tell him he does well. Luis reported that he has many friends, yet he has not been hanging out with them as much as he was before, and he don’t feel like being with his girlfriend, because he get too angry with her. He reported that he likes to watch sports on television. Luis describes himself as a good person, but don’t think he was when he was younger. Met all milestones; at time of assessment he reported his health to be within normal limits. Luis stated that he is not on any medication. His mother was diagnosed with depression following the family’s move from Puerto Rico. No history of psychiatric admissions or behavioral disorders. Luis is neatly dressed; wearing jeans and a t-shirt; he is of average height and weight. He was alert and oriented to person, place, and time. He was soft-spoken and his speech was at normal rate. Luis was very cooperative and rapport was easily established. He came to the testing session willingly to participate but reported he had one of those nights where he had trouble getting and staying asleep. On several occasions, he slumped back in his chair. He followed directions and were observed to have times of being somewhat sluggish in his responses.

Motivation Aspects to Job Selection

Motivation Aspects to Job Selection Motivation is derived from the latin word â€Å"movere† which means to move. Motivation is the process of moving from ones needs to drives and finally to incentives. Needs are identified because of a deficiency which may be physiological or psychological. Drives activate the behaviour for fulfilling the needs that were identified above. The behaviour which is performed because of drives cause results in a reward or an incentive which may be tangible or intangible. This report is about selecting a job that will motivate us and explaining the same using various motivation theories. We deliberated on the kind of jobs that would motivate us and came to the conclusion that we would wish to be management consultants in a reputed consultancy firm. After looking for vacancies in various job portals and company websites we came to the conclusion that joining Mckinsey and Company would be the best.The details of the job description and the company overview is discussed below. Job Description Junior Associate – McKinsey Company â€Å"As a consultant, you will join teams working with the top management of corporations on critical issues, identifying business opportunities, generating and evaluating solutions, and developing result-oriented change programs. You will also have the opportunity to contribute to the development of state-of-the-art management concepts and practices.† McKinsey Company is a global management consulting firm which started in the year 1926. It is one of the most trusted advisors to the worlds leading businesses, governments and institutions. One of the golden rules that Mckinsey follows is below which is beneficial to both employees as well as clients â€Å"We work with our clients as we do with our colleagues. We build their capabilities and leadership skills at every level and every opportunity. We do this to help build internal support, get to real issues, and reach practical recommendations. We bring out the capabilities of clients to fully participate in the process and lead the on-going work.† Motivation theory – Equity Model This cognitively based model is on the calculation of outputs received by an individual and the amount of input that he/she has put in to get the outputs. The inputs and outputs might be perceived differently by different individuals and hence it is measured relative between individuals. Age, sex, education, social status, organisational position, qualifications and how hard the person works are examples of perceived input variables. Outcomes consist primarily of rewards such as pay, status, promotion and intrinsic interest. Schematically this is represented in the 3 possible scenarios. If the perceived ratio is not equal to the others, he or she will strive to restore the ratio to equity. This striving to restore equity is used as the explanation of work motivation. The person may alter the inputs or outcomes, cognitively distort the inputs or outputs according to his or her scale. Maslow’s Needs Hierarchy and Theory of Motivation The Maslow’s model is one of the classic content theoretical models that explained motivational needs as a hierarchy. To simplify, he believed that once a given level of need is satisfied, it no longer serves to motivate. The next level of need has to be activated, which results in the motivation of an individual. The various levels of Maslow’s need can be understood by the below diagram with reference to a job or career. The job application that we are referring to is catering to the physiological and safety/security concerns that are required. The pay is quite high even at the entry levels with a base package of 20 lakhs p.a. with additional variable salary components that amount to 6 to 8 lakhs more. The next level i.e. the social level has been considered as an important aspect in the work culture of Mckinsey wherein they follow a collaborative approach. The associates work in small groups of 3 to 5 which consists of business analysts, associates and partners. The organisation is flat with few hierarchical levels and hence it makes easy for a person to approach others and get help in case of any issues. Our understanding of different industries and functions will grow exponentially as the teammates share their expertise. Well receive coaching and feedback throughout the engagement. In fact, consultants often find life-long mentors—and friendships—in their senior colleagues. The 3 levels of Maslow’s hierarchy are something which is readily satisfied by the job and the organisation. Hence focusing on the next level is the Esteem. Self Esteem as well as respect from others is an important aspect that needs to be addressed. Taking this job would provide us and opportunity to grow in the organisation. This is evident from the fact that Mckinsey recognises the performance of the individual and promotes them as seen in various posts from associates in forums. Formal performance reviews happen at the end of every project and associates with good analytical and people skills move up the ladder. The â€Å"Up or Out† approach makes sure that the performing people deserve to go to the top, right to the level of a CEO. Self-actualisation is indeed the most important aspect of this hierarchy where the professional tends to move towards satisfaction in life, both professional and personal. To cater to this need, Mckinsey creates a conducive environment where we will get many opportunities as described below. â€Å"Our private-sector work will put you at the center of the transformative forces sweeping business. We work in just about every industry and functional area you can imagine, with engagements that range from creating entirely new businesses, to leveraging leading-edge technologies, to reinventing manufacturing, to advising companies on the future of media and social sharing. Our public-sector and social-impact work is global in nature. We advise many of the worlds governments and NGOs on everything from re-imagining the delivery of education and the healthcare services to creating centers of local entrepreneurship.† Apart from professional aspirations, there is a scope of people for pursuing their passions such as singing, travelling and other personal wishes by opting for a programme known as the TIME-UP programme. The highlights of the programme are â€Å"Our â€Å"Take Time† program allows consultants to take time off between engagements to pursue personal interests and passions, whether that includes spending time with family or going on a dream trip. This â€Å"on and off† model allows consultants additional time to recharge without disrupting client work.† Making a difference in the world is a deep motivation. Porter Lawler Model Porter and Lawler suggested that motivation does not equal satisfaction or performance but they are all separate entities. They say that effort does not lead directly to performance but is directed by abilities, traits and by role perceptions. The rewards that follow and how they are perceived will determine satisfaction. Unlike the content theory, here performance leads to satisfaction. In lieu of the above theory, Mckinsey is cutting back their financial-incentive programs, but have used other ways of inspiring talent. The understand how to make their employees perform better and hence get satisfaction. Analogous to Porter-Lawler’s model we have:- Opportunity to perform- Mckinsey provides ample opportunities to its employees in order to enhance performance a chance to lead projects or task forces. Abilities Traits- As a company Mckinsey believes in its employees’ abilities and delegates work as per their abilities. Their belief helps the people to understand their potential and work towards better and better performance. Role Perceptions—Managers set expectations for the employees under them to perform better with specific roles. Effort Level and Direction of Effort- Praise from immediate managers for their work is found to be an effective way to boost the morale of the people. The employees are guided towards a direction so that their own effort is rightly appreciated and is fruitful for the company Self-Efficacy- Inculcating a strong sense of self-efficacy among the people helps them to develop deeper interest in the activities they perform. By Leadership attention-Managers go on one-on –one meeting with their team members to help them develop the desire to perform and produce a desired effect. Effort-Reward Probabilities- Team members are rewarded as per their performance. As budding managers this study helps us to realise that we need to inculcate the culture of performance driven satisfaction among our peers and subordinates. It is important for us, as managers, that we have belief in our team members and motivate them to perform better which will help us and them to gain satisfaction.

‘Big’ Data Science and Scientists

‘Big’ Data Science and Scientists If you could possibly take a trip back in time with a time machine and say to people that today a child can interact with one another from anywhere and query trillions of data all over the globe with a simple click on his/her computer they would have said that it is science fiction ! Today more than 2.9 million emails are sent across the internet every second. 375 megabytes of data is consumed by households each day. Google processes 24 petabyte of data per day. Now that’s a lot of data !! With each click, like and share, the worlds data pool is expanding faster than we comprehend. Data is being created every minute of every day without us even noticing it. Businesses today are paying attention to scores of data sources to make crucial decisions about the future. The rise of digital and mobile communication has made the world become more connected, networked and traceable which has typically resulted in the availability of such large scale data sets. So what is this buzz word â€Å"Big Data† all about ? Big data may be defined as data sets whose size is beyond the ability of typical database software tools to capture, create, manage and process data. The definition can differ by sector, depending on what kinds of software tools are commonly available and what sizes of data sets are common in a particular industry. The explosion in digital data, bandwidth and processing power – combined with new tools for analyzing the data has sparked massive interest in the emerging field of data science. Big data has now reached every sector in the global economy. Big data has become an integral part of solving the worlds problems. It allows companies to know more about their customers, products and on their own infrastructure. More recently, people have become extensively focused on the monetization of that data. According to a McKinsey Global Institute Report[1] in 2011, simply making big data more easily accessible to relevant stakeholders in a timely manner can create enormous value. For example, in the public sector, making relevant data more easily accessible across otherwise separated departments can sharply cut search and processing time. Big data also allows organizations to create highly specific segmentations and to tailor products and services precisely to meet those needs. This approach is widely known in marketing and risk management but can be revolutionary elsewhere. Big Data is improving transportation and power consumption in cities, making our favorite websites social networks more efficient, and even preventing suicides. Businesses are collecting more data than they know what to do with. Big data is everywhere; the volume of data produced, saved and mined is startling. Today, companies use data collection and analysis to formulate more cogent business strategies. Manufactures use data obtained from the use of real products to improve and develop new products and to create innovative after-sale service offerings. This will continue to be an emerging area for all industries. Data has become a competitive advantage and necessary part of product development. Companies succeed in the big data era not simply because they have more or better data, but because they have good teams that set clear objectives and define what success looks like by asking the right questions. Big data are also creating new growth opportunities and entirely new categories of companies, such as those that collect and analyze industrial data. One of the most impressive areas, where the concept of Big data is taking place is the area of machine learning. Machine Learning can be defined as the study of computer algorithms that improve automatically through experience. Machine learning is a branch of artificial intelligence which itself is a branch of computer science. Applications range from data mining programs that discover general rules in large data sets, to information filtering systems that learns automatically the user’s interests. Rising alongside the relatively new technology of big data is the new job title data scientist. An article by Thomas H. Davenport and D.J. Patil in Harvard Business Review[2] describes ‘Data Scientist’ as the ‘Sexiest Job of the 21st Century’. You have to buy the logic that what makes a career â€Å"sexy† is when demand for your skills exceeds supply, allowing you to command a sizable paycheck and options. The Harvard Business Review actually compares these â€Å"data scientists† to the quants of 1980s and 1990s on Wall Street, who pioneered â€Å"financial engineering† and algorithmic trading. The need for data experts is growing and demand is on track to hit unprecedented levels in the next five years Who are Data Scientists ? Data scientists are people who know how to ask the right questions to get the most value out of massive volumes of data. In other words, data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician. Good data scientists will not just address business problems; they will choose the right problems that have the most value to the organization. They combine the analytical capabilities of a scientist or an engineer with the business acumen of the enterprise executive. Data scientists have changed and keep changing the way things work. They integrate big data technology into both IT departments and business functions. Data scientist’s must also understand the business applications of big data and how it will affect the business organization and be able to communicate with IT and business management. The best data scientists are comfortable speaking the language of business and helping companies reformulate their challenges. Data science due to its interdisciplinary nature requires an intersection of abilities of hacking skills, math and statistics knowledge and substantive expertise in the field of science. Hacking skills are necessary for working with massive amount of electronic data that must be acquired, cleaned and manipulated. Math and statistics knowledge allows a data scientist to choose appropriate methods and tools in order to extract insight from data. Substantive expertise in a scientific field is crucial for generating motivating questions and hypotheses to interpret results. Traditional research lies at the intersection of knowledge of math and statistics with substantive expertise in a scientific field. Machine learning stems from combining hacking skills with math and statistics knowledge, but does not require scientific motivation. Science is about discovery and raising knowledge, which requires some motivating questions about the world and hypotheses that can be brought to data and tes ted with statistical methods. Hacking skills combined with substantive scientific expertise without rigorous methods can beget incorrect analysis. A good scientist can understand the current state of a field, pick challenging questions were a success will actually lead to useful new knowledge and push that field further through their work. How to become a Data Scientist ? No university programs in India have yet been designed to develop data scientists, so recruiting them requires creativity. You cannot become a big data scientist overnight. Data Scientist need to know how to code and should be comfortable with mathematics and statistics. Data Scientist need know machine learning software engineering. Learning data science can be really hard. They also need to know how to organize large data sets and use visualization tools and techniques. Data scientists need to know how to code either in SAS, SPSS, Python or R. Statistical Package for the Social Sciences (SPSS) is a software package currently developed by IBM is widely used program for statistical analysis in social science. Statistical Analysis System (SAS) software suite developed by SAS Institute is mainly used in advanced analytics. SAS is the largest market-share holder for advanced analytics. Python is a high-level programming language, which is the most commonly used by data scientist’s community. Finally, R is a free software programming language for statistical computing and graphics. R language has become a de facto standard among statisticians for developing statistical software and is widely used for statistical software development and data analysis. R is a part of the GNU Project which is a collaboration that supports open source projects. A few online courses would help you learn some of the main coding languages. One such course that is available currently is through the popular MOOCs website coursera.org. A specialization course offered by Johns Hopkins University through coursera helps you learn R programming, visualize data, machine learning and to develop data products. There are few more courses available through coursera that helps you to learn data science. Udacity is another popular MOOCs website that offers courses on Data Science, Machine Learning Statistics. CodeAcademy also offers similar courses to learn data science and coding in Python. When you start operating with data at the scale of the web, the fundamental approach and process of analysis must and will change. Most data scientists are working on problems that cant be run on a single machine. They have large data sets that require distributed processing. Hadoop is an open-source software framework for storing and large-scale processing of data-sets on clusters of commodity hardware. MapReduce is this programming paradigm that allows for massive scalability across the servers in a Hadoop cluster. Apache Spark is Hadoops speedy Swiss Army knife. It is a fast -running data analysis system that provides real-time data processing functions to Hadoop. It is important that a data scientist must be able to work with unstructured data, whether it is from social media, videos or even audio. KDnuggets is a popular website among data scientist that mainly focuses on latest updates and news in the field of Business Analytics, Data Mining, and Data Science. KDnuggets also offers a free Data Mining Course the teaching modules for a one-semester introductory course on Data Mining, suitable for advanced undergraduates or first-year graduate students. Kaggle is a platform for data prediction competitions. It is a platform for predictive modeling and analytics competitions on which companies and researchers post their data and statisticians and data miners from all over the world compete to produce the best models. Kaggle hosts many data science competitions where you can practice, test your skills with complex, real world data and tackle actual business problems. Many employers do take Kaggle rankings seriously, as they can be seen as pertinent, hands-on project work. Kaggle aims at making data science a sport. Finally to be a data scientist you’ll need a good understanding of the industry you’re working in and know what business problems your company is trying to solve. In terms of data science, being able to find out which problems are crucial to solve for the business is critical, in addition to identifying new ways should the business should be leveraging its data. A study by Burtch Works[3] in April 2014, finds that data scientists earn a median salary that can be up to 40% higher than other Big Data professionals at the same job level. Data scientists have a median of nine years of experience, compared to other Big Data professionals who have a median of 11 years. More than one-third of data scientists are currently in the first five years of their careers. The gaming and technology industries pay higher salaries to data scientists than all other industries. LinkedIn, a popular business oriented social networking website voted statistical analysis and data mining the top skill that got people hired in the year 2014. Data science has a bright future ahead there will only be more data and more of a need for people who can find meaning and value in that data. Despite the growing opportunity, demand for data scientist has outpaced supply of talent and will for the next five years. [1] McKinsey Global Institute, â€Å"Big data: The next frontier for innovation, competition, and productivity†, June 2011 [2] Thomas H. Davenport, D.J. Patil, â€Å"Data Scientist: The Sexiest Job of the 21st Century†, Harvard Business Review, October 2012 [3] Burtch Works â€Å"Big Data Career Tips† http://www.burtchworks.com/big-data-analyst-salary/big-data-career-tips/, accessed December 2014

All About the Philippines :: essays research papers

The first inhabitants of the Philippines arrived from the land bridge from Asia over 150,000 years ago. Throughout the years, migrants from Indonesia, Malaysia, and other parts of Asia made their way to the islands of this country. In the fourteenth century, the Arabs arrived and soon began a long tradition of Islam. Many Muslims are still living in the Philippines today.   Ã‚  Ã‚  Ã‚  Ã‚  In 1521, Magellan claimed the land for Spain, but was killed by local chiefs who did not want Spain’s inhabitance. However, the Spanish returned in 1543 and named the land Filipinas after King Philip II. Spain soon after began their control. At the time of the Spanish American War the colonial government in the Philippines was administered by a Governor-General selected in Spain. The Philippine islands were used to reward the king’s favorites who could return home enormous fortunes from natives and foreign immigrants via a system of taxation that savored of blackmail and confiscation. The Governor-General had a cabinet composed of the Archbishop of Manila, the Captain-General of the army and the Admiral of the navy stationed in the colonies. The administrative power lay with the Governor-General and the Archbishop, and the religious orders of the Spanish Catholic Church were the practical controllers.   Ã‚  Ã‚  Ã‚  Ã‚  The climate of the Philippines, which is tropical, subjected to violent monsoons, seasons of drenching rains, and an almost intolerable heat lasting from March to July, has made it necessary to change continually the Spanish administrators. By 1571, the country had control over the islands, except for any Islamic areas.   Ã‚  Ã‚  Ã‚  Ã‚  The Filipinos lived in settlements called barangays before the colonization of the Philippines by the Spaniards. As the unit of government, a barangay consisted from 30 to 100 families. It was headed by a datu and was independent from the other groups. Usually, several barangays settled near each other to help one another in case of war or any emergency. The position of datu was passed on by the holder of the position to the eldest son or, if none, the eldest daughter. However, later, any member of the barangay could be chieftain, based on his talent and ability. He had the usual responsibilities of leading and protecting the members of his barangay. In turn, they had to pay tribute to the datu, help him till the land, and help him fight for the barangay in case of war. There were four classes of society.

We Need Tough Laws to Protect the Environment Essay examples -- Enviro

With Adam Smith and Milton Friedman among its illustrious fathers, the theory of the free market is a widely accepted and respected one today in America. It advocates the concept of a market as a self-regulating entity. By the working of natural principles such as free competition, consumer sovereignty, and maximization of the individuals' self-interest, the market is able to decide the allocation, utilization, and distribution of resources most fairly and efficiently. This characteristic of the market, known as the "Invisible Hand", is constantly hailed as one of the most imperative mechanisms of a capitalistic economy. At the same time, it is recognized that the free market does have its few but important limitations, the most notable of which are the natural emergence of monopoly, the existence of positive and negative externalities, the need for public goods that would not be provided by the market. Such instances necessitate the interference from institutions outside of the market, most commonly the government. The degradation of the earth's environment belongs to the last two groups of market failure types. Most proponents of the free market acknowledge that a clean environment can be considered as a public good because it defies the exclusionary principle; and that conversely, environmental degradation is a negative externality. Thus, a certain reasonable degree of outside intervention is required for the cause of environmental protection. The definition of this "reasonable level of outside interference" may vary depending on personal beliefs, but generally it can be characterized as "the less, the better." Private organizations' efforts are emphasized and preferred to governmental regulations and restrictions. Even w... ... Environmental Racism. Crisis in American Institutions. Edited by Jerome H. Skolnick and Elliot Currie. Allyn and Bacon. 2000. Commoner, Barry. "Why We Have Failed." Crisis in American Institutions. Edited by Jerome H. Skolnick and Elliot Currie. Allyn and Bacon. 2000. "Free Market Environmentalism". Edited by Robert Knautz. Policy Spotlight. Volume 1. Number 5. May-June 1997. Gelbspan, Ross. The Heat Is On. Crisis in American Institutions. Edited by Jerome H. Skolnick and Elliot Currie. Allyn and Bacon. 2000. Inter Press Service. "Big Corporations are Getting Bigger and Personal". December 4, 2000. March 5, 2001. "Origins of Fossil Fuel Disinformation Campaigns". The Heat Is Online. March 5, 2001. Snell, Bradford Curie. "American Ground Transport". Transport. 1973. Ideas & Institutions in American Society Course Reader, New York University. Spring 2001.

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Information for patients The department of Obstetrics & Gynaecology looks after only women patients. Obstetrics deals with pregnancy and child birth. An obstetrician gives pre pregnancy counseling, looks after the woman and her baby during pregnancy, helps with child birth and looks after the woman for six weeks after delivery. A gynaecologist looks after women with diseases of the reproductive system. These include period problems, infections, benign tumours like fibroids and ovarian cysts and cancers.Women wanting to conceive are looked after by the Reproductive Medicine Unit which will look after the gynaecological problems of these women also. The department of Obstetrics and Gynaecology now have five units. The outpatient days and contact details of the five units are given below. |OG unit 1 |  Ã‚  Ã‚  Gynaecology and Gynae cancer | |Phone No: |  Ã‚  Ã‚  0416 – 2283395 | |Email : |  Ã‚  Ã‚  [email  protected] ac. n | |OPD days : |  Ã‚  Ã‚  Mondays & Thurdays | |   |  Ã‚  Ã‚  Menopause clinic on Wednesday afternoon | |Faculty : |  Ã‚  Ã‚  Dr. Abraham Peedicayil (Professor & Head of the Unit) | |   |  Ã‚  Ã‚  Dr. Alice George (Professor ) | |   |  Ã‚  Ã‚  Dr.Rachel Chandy (Professor) | |   |  Ã‚  Ã‚  Dr. Anitha Thomas (Asst. Professor) | |   |   | |OG unit 2 |  Ã‚  Ã‚  Gynaecology and Urogynaecology | |Phone No: |  Ã‚  Ã‚  0416 – 2283397 |Email : |  Ã‚  Ã‚  [email  protected] ac. in | |OPD days : |  Ã‚  Ã‚  Tuesdays & Fridays | |   |  Ã‚  Ã‚  Female Continence clinic on Wednesday | |Faculty : |  Ã‚  Ã‚  Dr. Aruna Kekre (Professor & Head of the Unit) | |   |  Ã‚  Ã‚  Dr.Lilly Varghese (Professor) | |   |   | |OG unit 3 |  Ã‚  Ã‚  Obstetrics & Gynaecology | |Phone No: |  Ã‚  Ã‚  0416 – 2283399 | |Email : |  Ã‚  Ã‚  [email  protected] c. in | |OPD days : |  Ã‚  Ã‚  Wednesday & Saturday | |Faculty : |  Ã‚  Ã‚  Dr. Annie Regi (Professor & Head of the Unit) | |   |  Ã‚  Ã‚  Dr. Jessie Lionel (Professor – On leave) | |   |  Ã‚  Ã‚  Dr.Elsy Thomas (Asst Professor) | |   |   | |OG unit 4 |  Ã‚  Ã‚  Obstetrics | |Phone No: |  Ã‚  Ã‚  0416 – 2286185 | |Email : |  Ã‚  Ã‚  [email  protected] ac. in | |OPD days : |  Ã‚  Ã‚  Tuesday & Friday | |Faculty : |  Ã‚  Ã‚  Dr.Ruby Jose (Professor & Head of the Unit) | |   |  Ã‚  Ã‚  Dr. Reeta Vijayaselvi (Asst Professor) | |   |   | |OG unit 5 |  Ã‚  Ã‚  Obstetrics | |Phone No: |  Ã‚  Ã‚  0416 – 2286172 | |Email :   Ã‚  Ã‚  [email  protected] ac. in | |OPD days : |  Ã‚  Ã‚  Monday & Thursday | |Faculty : |  Ã‚  Ã‚  Dr. Jiji Elizabeth Mathews (Professor & Head of the Unit) | |   |  Ã‚  Ã‚  Dr. Bivas Biswas (Asst Professor -On leave) | |   |   |Special clinics run by the department Female Continence Clinic  Ã¢â‚¬â€œ Wednesday – 8. 00 am , Room 2 & 3 in OG OPD Caters to women with urinary and defaecation problems Menopause clinic  with gynaecologists and endocrinologists – Caters to women after menopause – Wednesday 2. 30 p. m. , Room 22 & 23 in OG OPD Perinatal Medicine Clinic  Ã¢â‚¬â€œ Wednesday (with obstetricians, Neonatologists and geneticist) Caters to women who have had babies with birth defects, repeated abortions, still births, who are worried about these problems recurring. Wednesday 2. 00 p. m. , Room 2 in OG OPD

About Love Essay

Overpopulation[edit source | editbeta] Further information: Family planning in India and Demographics of India India suffers from the problem of overpopulation. The population of India is very high at an estimated 1.27 billion.[1][2][3] Though India ranks second in population, it ranks 33 in population density. Indira Gandhi, Prime Minister of India, had implemented a forced sterilization programme in the early 1970s but the programme failed. Officially, men with two children or more were required to be sterilised, but many unmarried young men, political opponents and ignorant, poor men were also believed to have been affected by this pogramme. This program is still remembered and regretted in India, and is blamed for creating a public aversion to family planning, which hampered Government programmes for decades.[4] See more: Ethnic groups and racism essay Definition of ‘Social Economics’ Problems Socio Economics Problems focuses on the relationship between social behavior and economics. Social economics examines how social norms, ethics and other social philosophies that influence consumer behavior shape an economy, and uses history, politics and other social sciences to examine potential results from changes to society or the economy. 1. Overpopulation : India suffers from the problem of overpopulation. Though India ranks second in population, it ranks 33 in terms of population density below countries such as The Netherlands, South Korea and Japan. To cure this problem, Indira Gandhi, Prime Minister of India, had implemented a forced sterilization programme in the early 1970s but failed. Officially, men with two children or more had to submit to sterilization, but many unmarried young men, political opponents and ignorant, poor men were also believed to have been sterilized. This program is still remembered and criticized in India, and is blamed for creating a wrong public a version to family planning, which hampered Government programmes for decades. Overpopulation Overpopulation is becoming one of the most preeminent problems facing human civilization. This complicated, pervasive issue will come to be a problem of the utmost importance for people of all races, religions, and nationalities. Our planet now provides for approximately 5.8 billion people, with projections of around 10 billion by the year 2050. Two billion of these are extremely poor, the poorest of which live in absolute poverty and misery. One very serious effect of the population explosion is its detrimental effects on the global environment. Increasing amounts of food, energy, water, and shelter are required to fulfill the needs of human society. Much of our energy is derived from the burning of fossil fuels-releasing millions of metric tons of toxins into the atmosphere annually. The amount of land required for food production will grow increasingly larger, while the amount of available land will grow increasingly smaller. The affects of overpopulation on human society are many. Suffering from a lack of resources, people are often driven to war when they become too numerous for their available resources. Ethnic and racial differences will grow increasingly frequent and unresolvable. Increasing numbers in urban areas will lower quality of life in cities around the world. The precipitators of this complex issue are unlimited. Factors such as poverty, food distribution, and government corruption are all important aspects. No one will be unaffected by the repercussions of an overpopulated world. This highly sensitive and complex issue demands the attention of all who reside upon this planet, particularly those who have the ability to work for change.