HUMAN DEVELOPMENT INDEX HOW DO WE Geographers agree that the most effective tool to measure quality of life around the world is the Human Development Index (HDI). Every year, the UN gathers data from its member countries and ranks their HDI scores. In each country, it considers indicators in three key areas of human development: • longevity: the average life expectancy of the people in a country • knowledge: the average number of years that adults have attended school, and the expected years of schooling that a child just entering school will complete • country’s income: the total income of a country in one year, divided by the number of people (Gross National Income [GNI] per person) Together, the indicators give a “snapshot” of the quality of life of the people in each country. A country with top marks for every indicator would have an HDI score of 1.000. In the 2014 Human Development Report, the world HDI was 0.702. Compare this to the scores of the countries listed in Figure 5.14. For example, Qatar’s GNI is well above Canada’s and yet Canada has a higher HDI ranking. What kind of questions does this make you ask? COMPARE QUALITY OF LIFE? Country Rank HDI Score Human Development Index (HDI) the results of an annual evaluation of countries made by looking at life expectancy, literacy, and income Gross National Income (GNI) per person the total, or gross, income of a country in one year, divided by the number of people Life Expectancy (years) Adult Schooling (years) Expected Child Schooling (years) Average Income per Person ($) Very High HDI (0.800 to 1.000) Many people compare their quality of life with the quality of life of others living within their country. They also compare the overall quality of life in their country to the overall quality of life of other countries. Country leaders also compare. This can help them to decide on priorities and set goals for developing their country and improving the quality of life for their citizens. For example, they may prioritize healthcare or increased economic development. Some leaders aim to bring their people freedom from unjust treatment. In South Africa, decades of widespread racism affected the quality of life of the majority of its Black citizens. In 1994, Nelson Mandela ran for president to promote equality and freedom and encourage change. He won the election (Figure 5.13). FIGURE 5.13 For decades, Nelson Mandela struggled to end South Africa’s racist policies, even from prison. In the 1994 election, all citizens were allowed to vote for the first time. Mandela was elected president. 150 UNIT 2: Global Inequalities: Economic Development and Quality of Life 1 0.944 81.5 12.6 17.6 63 909 Canada 8 0.902 81.5 12.3 15.9 41 887 Qatar 31 0.851 78.4 9.1 13.8 119 029 High HDI (0.700 to 0.799) Uruguay 50 0.790 77.2 8.4 15.5 18 108 Malaysia 62 0.773 75.0 9.5 12.7 21 824 China 91 0.719 75.3 7.5 12.9 11 477 WORLD I wonder what changed in South Africa so that a person who was once in jail could become president? 0.702 Medium HDI (0.550 to 0.699) USING INDEXES TO MEASURE QUALITY OF LIFE Indexes help us understand development on a global scale. An index summarizes data made from a set of observations. Examples of indexes created to measure quality of life are the Human Development Index, the Happy Planet Index, the World Happiness Report, and the Gross National Happiness Index. Each index focuses on different factors and indicators. Norway Maldives 103 0.698 77.9 5.8 12.7 10 074 Vietnam 121 0.638 75.9 5.5 11.9 4 892 Bangladesh 142 0.558 70.7 5.1 10.0 2 713 Low HDI (0.000 to 0.549) How can an index help us to identify geographic patterns in quality of life? Nepal 145 0.540 68.4 3.2 12.4 2 194 Sudan 166 0.473 62.1 3.1 7.3 3 428 Niger 187 0.337 58.4 1.4 5.4 873 FIGURE 5.14 This table lists some values for the HDI and its components from the Human Development Report 2014. The HDI data was collected in 2013. NEL NEL CHAPTER 5: Understanding Quality of Life 151 SCATTER GRAPHS Country A scatter graph shows a relationship between two sets of data. Geographers use scatter graphs to analyze data about many themes, including quality of life. Each axis on a scatter graph represents a different set of data. So when you read a scatter graph, you first check to see what the two sets of data are. The points on the graph are where the values from each set of data intersect. Check to see if the data form a pattern. If there is a pattern, you know there is a relationship between the two sets of data. Look at the scatter graphs in Figure 5.15. Figure 5.15A shows a positive pattern—the data increases along the x axis and the y axis. Figure 5.15B shows a negative pattern—as one set of data increases (x axis), the other set decreases ( y axis). There is no pattern in Figure 5.15C. If a graph has no pattern, referred to as a random pattern, there is no connection between the two sets of data. When you construct a scatter graph, you choose two sets of data. You refer to the range of each set of data to decide which intervals to mark. For example, in Figure 5.16, healthcare spending data ranges from 3.49 to 11.18. One axis on your graph would need to include intervals between 0 and 12. You label each axis based on the information it will show. A B Positive y C Negative y Healthcare Spending (% of GDP) 12 11 Angola 3.49 51.9 Bulgaria 7.27 73.5 Canada 11.18 81.5 Iran 5.95 74.0 Mongolia 5.26 67.5 10.86 82.6 Switzerland Healthcare Spending and Life Expectancy in Selected Countries, 2014 Life Expectancy (years) FIGURE 5.16 Percent of GDP spent on healthcare and years of life expectancy in selected countries, 2014 Healthcare spending (% of GDP) ANALYZING AND CREATING FIGURE 5.17 Scatter graph showing percent of GDP spent on healthcare and years of life expectancy in selected countries, 2014 Switzerland 10 9 8 Bulgaria 7 6 Iran Mongolia 5 4 Angola 3 0 50 x 0 Random STEP 2 FIGURE 5.15 These scatter graphs show three different patterns: positive, negative, and random. x 0 Draw the y axis starting from 0 on the x axis. Number the lines from 0 to 1.0 in intervals of 0.1. Label the y axis “HDI score.” Plot the data in Figure 5.18. Put a red dot where the two values for each country intersect. Do not join the dots. Beside each dot, print the name of the country. x What is the relationship between the data? Use the information you have read on page 145 to explain any connection between the data. 152 STEP 1 Does the data show a positive, negative, or random pattern? STEP 3 UNIT 2: Global Inequalities: Economic Development and Quality of Life Draw an x axis on graph paper. Number the lines from 0 to 14 in intervals of 1. Label the x axis “Adult schooling (years).” Give your graph an appropriate title. STEP 5 HOW TO ANALYZE A SCATTER GRAPH STEP 2 90 STEP 3 STEP 6 Examine the data in Figure 5.16 and the scatter graph in Figure 5.17, which was created from this data. What are the two sets of data shown on the graph? What does each dot on the graph represent? 70 80 Life expectancy (years) STEP 1 STEP 4 0 60 HOW TO CREATE A SCATTER GRAPH Look at the data in Figure 5.18. What does the data represent? What are the two sets of data that are included? y Canada What pattern is created by the dots? What does this tell you about the connection between HDI scores and the number of years that adults have gone to school? Norway Canada Qatar Chile Sri Lanka Botswana Vietnam Ethiopia HDI Score 0.944 0.902 0.851 0.822 0.750 0.683 0.638 0.435 Adult Schooling (years) 12.6 12.3 9.1 9.8 10.8 8.2 5.5 2.4 FIGURE 5.18 HDI scores and years of adult schooling in selected countries, 2014 NEL NEL CHAPTER 5: Understanding Quality of Life 153 HAPPINESS INDEXES FOCUS ON INTERPRET AND ANALYZE As you continue your geographic education, you need to develop certain skills. These skills include interpreting and analyzing geographic data. Geographers use tools such as tables, graphs, diagrams, and maps to describe and organize data. This makes it easier to look for patterns and analyze trends, issues, and perspectives. TRY IT INTERPRETING AND ANALYZING A TABLE When interpreting and analyzing a table, ask yourself the following questions: • What is the source of the data? Why was the data created? • What is the title of the table, and what are the headings? What does the data represent? • What significant patterns or differences can you see for each category? What are your best guesses based on the evidence? 1. In Figure 5.19, a high score is considered good for life expectancy and HPI score. Explain whether this is true for ecological footprint and for experienced well-being, and explain why. 2. Use a graphic organizer, such as a web, to interpret and analyze the information in Figure 5.19. In the centre of your organizer, write the table’s title. For each of the table’s three categories, summarize what you see. For example, [country] has the highest life expectancy and [country] has the lowest. Note the connections to the HPI. For example, [country] has high life expectancy and high experienced well-being, but a low HPI. 3. Select two countries that seem to have a disconnect between their HPI scores and the three other factors. Explain this disconnect using the data in the table. CASE STUDY: HAPPY PLANET INDEX The United Kingdom’s New Economics Foundation (NEF) researches the connections among the economy, the environment, and a society’s well-being. The NEF created the Happy Planet Index (HPI) to measure three factors: life expectancy, ecological footprint, and people’s views of their experienced well-being. Ecological footprint is the amount of land needed by a country to support a citizen’s daily living on Earth. The experienced well-being data reflects people’s responses to a survey asking how satisfied they are with their daily lives. Connecting well-being to the use of natural resources allows an overall look at a country’s sustainability and also the planet’s sustainability. The data in the 2012 HPI report showed that no country comes close to a high degree of sustainability. Why is this? Mainly, people are using too many natural resources. 154 Happy Planet Index Data and Scores for Several Countries, 2012 Life Expectancy Ecological Footprint Experienced Well-Being (out of 10) HPI Score (out of 100) Costa Rica (1) 79.3 2.5 7.3 64.0 Vietnam (2) 75.2 1.4 5.8 60.0 Colombia (3) 73.7 1.8 6.4 59.8 Pakistan (15) 65.4 0.8 5.3 54.1 India (32) 65.4 0.9 5.0 50.9 China (60) 73.5 2.1 4.7 44.7 Canada (65) 81.0 6.4 7.7 43.6 Singapore (90) 81.1 6.1 6.5 39.8 United States (105) 78.5 7.2 7.2 37.3 Qatar (149) 78.4 11.7 6.6 25.2 Country (rank out of 151) You read about the Happy Planet Index on page 154. The World Happiness Report, created by the UN, also considers more than economic factors when assessing quality of life. It suggests that six factors seem to be responsible for differences in happiness: healthy life expectancy, having someone to count on, freedom to make life choices, fair treatment in society, generosity of fellow citizens, and household income. In 2013, the top six countries deemed to be happy were Denmark, Norway, Switzerland, the Netherlands, Sweden, and Canada. Bhutan created the Gross National Happiness Index (Figure 5.20) as another way to measure quality of life. It surveys its people to assess their spiritual, physical, and social well-being, and it measures the health of the natural environment. The survey divides happiness into four categories: unhappy, narrowly happy (slightly happy), extensively happy (happy in many areas), and deeply happy (very happy). In 2010, the results showed that 10.4 percent of the people were unhappy; 47.8 percent were narrowly happy; 32.6 percent were extensively happy; and 8.3 percent were deeply happy. The results also showed that men were happier than women, and urban dwellers were generally happier than rural dwellers. The country uses the results of the data to try to develop policies to increase happiness. MEASURING INEQUALITIES Currently there are no indexes that measure all aspects of quality of life. Also, many indexes, such as the HDI, create a score for a whole country. They do not measure levels of inequality within a country. For example, life expectancy of Aboriginal peoples in Canada is six to nine years below the Canadian average, and income is about 30 percent lower. However, the UN’s Inequality-adjusted Human Development Index (IHDI) does measure inequalities within a country. When Canada is measured by the IHDI, its HDI ranking drops. In 2013, Canada’s HDI was 0.902 but its IHDI was lower at 0.833. Aboriginal peoples are working hard to narrow the gaps between their quality of life and the Canadian average. Changes are slowly happening. How would I try to calculate happiness in my country? Inequality-adjusted Human Development Index (IHDI) the results of an annual evaluation of countries made by looking at life expectancy, income, and literacy, and how these are distributed among the population CHECK-IN 1. EVALUATE AND DRAW CONCLUSIONS Some people argue that the HDI is not a good tool for measuring quality of life. They say that it does not examine conditions that affect people’s satisfaction with their life or their overall happiness. Evaluate this argument with a partner and arrive at a conclusion together. FIGURE 5.19 This table shows the data used to calculate the results for several countries on the 2012 Happy Planet Index. The life expectancy data is from the Human Development Report 2011. UNIT 2: Global Inequalities: Economic Development and Quality of Life FIGURE 5.20 Bhutan created the Gross National Happiness Index to measure the quality of life of its citizens. Spiritual well-being of its people and health of the natural environment are measured on the index. NEL NEL 2. INTERRELATIONSHIPS Create a graphic organizer to identify connections between all of these three sets of indicators: • life expectancy and gross national income per person • gross national income per person and average years of adult schooling • average years of adult schooling and life expectancy CHAPTER 5: Understanding Quality of Life 155