Economic Inequality Between Regions of Turkey

ECONOMIC INEQUALITY BETWEEN REGIONS OF TURKEY

Selen Demircioğlu

İstanbul Bilgi Üniversitesi

Abstract

This study aims to point out that there are huge rate of economic inequality between regions of Turkey. To do so, it insists mostly on the income differences. It defines and explains the main terms about the topic which are income inequality, Gini coefficient and poverty. It focuses on regional units such as general occupation, the Gini coefficient and population-based data of the regions of Turkey. It also contains general data such as poverty due to the social strata, in order to see and understand economic inequality within a wide perspective. The given data are analyzed with comparing in each term. It is concluded that the economic inequality between regions is a serious problem which continues to grow bigger.

Keywords: regional income inequality, poverty, social strata

Introduction

Economic inequality is a topic which is being discussed all over the world. It is treated with attention because it is to be the main measure for a country’s developmental status. Developed countries have a lower rate of economic inequality therefore the quality of life remains high. For example, according to Eurostat (2004), in Denmark where the poverty rate is only %10 while in Turkey it is %25. (as in cited in Dansuk, Erdoğan & Özmen, 2008, p.4) “The average household net-adjusted disposable income per capita is 25 172 USD a year”(Organization for Economic Co-operation and Development [OECD], 2014). This rate is higher than the OECD average.

Economic inequality is defined as “the unequal distribution of household or individual income across the various participants in an economy.” (Investopedya, Income Inequality, n.d) Income inequality refers to a percentage of total income proportional to the population. For example, if a small part of the population controls a huge proportion of the income of a country, this economic condition belonging to the country is considered as unequal. It is also considered as an important measurement of “fairness”. Which economic distribution is fair for every member of the society is still a remaining question mark.

1. General Occupation of the Regions

When the topic relates to the economic inequality between the regions of Turkey, it is important to understand economic status of each region. To do so, it is necessary to examine the general occupation of each region. Afterward, the occupation will be examined according to its income rate proportionally to the population. It also makes a significant comprehend about poverty in each region divided as urbanized and rural, so that it can claim and point out the economic inequality between these regions.

Table 1: Population, Income and Poverty Rate

Social Strata Population Population (%) Number of Poor Poverty
(%)
Employers

280,864

0.41
High-skilled workers 1,632,237 2.36 0.95
Professionals 110,75 0.16
Big Tradesmen 1,747,507 2.53
Skilled Workers 5,935,230 8.58 4.51
Small Tradesmen 4,396,695 6.35 2.74
Unskilled Workers 20,239,433 29.25 5,486,745 33.76
Non-active People 6,871,146 9.93 2,781,550 17.12
Small Farmers 3,332,848 1,117,373 6.88
Landless/Small Property/Agricultural Workers 8,485,803 12.26 3,953,253 24.33

Source: SIS (2004) (as cited in Dansuk et al., 2008)

1.1 Regional Occupation

As Özmucur and Silber (2002) noted that Marmara, Aegean and Mediterranean regions are the richest regions because these areas are urbanized while Eastern and the Southern Anatolia were noted as the poorest rural regions. (p.33) As it can be interpreted from the Table 1, the main occupation of the urbanized regions (employers, high-skilled workers, professionals, big tradesmen) have less percentage of poverty (%0,95 of high-skilled workers), in opposition to small farmers (%6,88), landless/small property/agricultural workers (%24,33) who are mainly located at rural regions. As the risk and the rate of poverty increases, the economic inequality between urbanized and rural regions also gets bigger.

1.2 Disproportion

In Table 1, It is remarkable that even if the employers, professionals and big tradesmen are a very small part of the population (%3,1 of the total population), they don’t have a significant rate of poverty. In contrast, unskilled workers and landless/small property/agricultural workers make up the greater part of the population (%41.51), they have a massive rate of poverty (%58,09). It is an indicator for a huge economic inequality because a small part of the population gains the most of the total income, as the greater part of the population suffers from poverty even if they have jobs. To even more accentuate the inequality, it can be said that 4 out of 10 non-active people are poor while 4,5 out of 10 agricultural workers suffer through poverty.

2. Regional Statistics

Regional inequality is related to region’s population and its income. As the income per person doesn’t rate close with the real income of every member of that region, it refers that inequality in this region has a higher rank.

2.1 Eastern Turkey

In the Table 2, we can notice that the highest rate of poverty belongs to Mardin which is in the South East Anatolia, with %82,37. Other cities that also have a high level of poverty can be listed as Van with a rate of %57,77 and Ağrı with %47.31. These two cities present in the Eastern Anatolia.
It can be clearly seen that the poorest regions of Turkey are in the East part of the Turkey. Furthermore, according to TURKSTAT (2004-2011), Eastern Anatolia (Ağrı, Kars, Iğdır, Ardahan) industry has the lowest rate of gross value added followed by Van, Muş, Bitlis and Hakkari which are also part of the Eastern Anatolia.

2.2 Western Turkey

When it comes to Eastern Turkey, as it can be seen in the Table 2, İstanbul has the lowest rate of poverty with only %5 followed by other big cities such as Tekirdağ (%10.80) and İzmir (%10.83). As the TURKSTAT (2004-2011) claims that in 2004, İstanbul has the highest rate of gross value added in industry, followed by İzmir, Kocaeli, Sakarya and Bursa; all are located in Marmara region.

Table 2: Regional Distribution of Poverty 

Regions Population Income per person
(TL annually)
Number of Poor People Rate of Poverty (%)
İstanbul 10,707,956

3,661,310,291

565,074

5.28

Antalya

2,535,363

2,581,810,923

187,667

7.40

Ankara

4,044,175

2,362,634,294

413,708

10.23

Tekirdağ

1,339,887

2,870,185,864

144,659

10.80

İzmir

3,483,026

2,311,115,449

377,216

10.83

Kocaeli

2,789,950

1,774,515,389

356,365

12.77

Balıkesir

1,535,328

2,518,143,771

203,843

13.28

Bursa

3,123,297

2,309,979,237

430,956

13.80

Aydın

2,597,724

3,111,922,218

442,303

17.03

Trabzon

3,111,287

1,827,938,551

567,854

18.25

Zonguldak

945,020

2,938,729,335

193,540

20.48

Kırıkkale

1,715,913

1,964,405,518

390,956

22.78

Adana

3,691,600

2,046,209,690

873,817

23.67

Manisa

3,097,208

1,846,995,419

757,576

24.46

Malatya

1,751,233

1,725,634,962

436,230

24.91

Konya

2,435,727

1,891,558,887

646,111

26.53

Hatay

2,766,317

1,862,658,508

784,246

28.35

Kayseri

2,537,035

1,486,790,405

732,334

28.87

Kastamonu

828,787

2,029,852,549

243,527

29.38

Gaziantep

2,093,679

1,545,536,200

734,619

35.09

Erzurum

1,333,751

1,413,199,782

499,014

37.41

Samsun

2,997,519

1,652,383,843

1,303,217

43.48

Ağrı

1,120,369

1,059,872,721

530,007

47.31

Van

2,015,285

1,252,456,329

1,164,255

57.77

Şanlıurfa

2,862,487

951,425,201

1,841,536

64.33

Mardin

1,735,643

673,763,128

1,429,660

82.37

Source: SIS (2004) (as cited in Dansuk, et al., 2008)

3. Gini Index

The most popular and used measurement for economic inequality is the Gini Coefficient also known as the Gini Index. It indicates “the gap between the rich and the poor”. (Investopedya, Gini Index, n.d) The lowest rate of Gini index is 0 while the highest rate is 1. The higher Gini index gets, the more there is a disproportional distribution of the income for a group. As an illustration, we can say that if the Gini index rates 0 there is a total equality. In contrast, if the Gini index is measured as 1, it is said to be a perfect inequality. In addition, Gini index is in direct proportion to poverty rate. (Dansuk et al., 2008)

3.1 Comparison

Table 3: Gini Coefficient

Regions

2006

2013

Istanbul 0,375 0,392
West Marmara 0,350 0,337
Aegean 0,426 0,370
East Marmara 0,392 0,322
West Anatolia 0,413 0,396
Mediterranean 0,421 0,399
Central Anatolia 0,342 0,342
West Black Sea 0,372 0,331
East Black Sea 0,378 0,315
North East Anatolia 0,381 0,398
Central East Anatolia 0,404 0,373
South East Anatolia 0,396 0,380

Source: TURKSTAT (2006-2013)

According to Table 3, the Gini index of İstanbul and North East Anatolia have grown while the others have decreased. Marmara region still has the lowest rates while Eastern regions have higher rate for inequality.

3.2 Analysis

As the Gini coefficient also shows the rank of poverty, we can say that other regions such as West Black Sea and East Black Sea regions are in the stage called ”maturation” in order to be developed regions based on Kuznets (1995) suggestion that claimed economic inequality rises with the early years of economic development, then declines as the developmental process continues. (as in cited in Özmucur & Silber, 2002, p.1) Yet, the level of development isn’t equal between regions of Turkey, thus the Gini index differs according to regions.

Conclusion

We have discussed economic inequality between regions of Turkey in order to understand the reason behind the unequal developmental stage of Turkey. The causes of economic inequality between region’s Turkey are unequal development of cities, unequal urbanization followed by immigration, uneven distribution of the income in portion to population. This situation can be seen as a way of growth or can be treated as a social-economic problem. It differs according to different perspectives which will continue to be discussed.

References

Dansuk, E., Erdoğan, G., & Özmen, M. (2008, April 1). Poverty and social stratification at the regional             levels of Turkey. Türk-iş Dergisi.
Investopedia. (n.d). Gini Index. Retrieved from
http://www.investopedia.com/terms/g/gini-index.asp
Investopedia. (n.d). Income Inequality. Retrieved from
http://www.investopedia.com/terms/i/incomeinequality.asp
OECD. (2014). Denmark. Retrieved from
http://www.oecdbetterlifeindex.org/countries/denmark/
Özmucur, S., Silbert, J. (2002). Spatial income inequality in Turkey and the impact of internal migration
TURKSTAT. (2004-2011). Regional gross value added at current basic prices – by kind of
economic 
activity

Reklamlar

CMN – FINAL PROJECT

REFERENCES

      1. Gürsel, S. (2013, October 28). Income inequality: A highly controversial subject. Retrieved December 10, 2014, from http://www.todayszaman.com/columnist/seyfettin-gursel/income-inequality-a-highly-controversial-subject_329992.html
      2. How’s life in your region? Insights from income distribution and poverty in OECD regions. (2014, July 1). Retrieved December 8, 2014, from http://www.oecd.org/els/soc/OECD2014-Insights-Income-Distribution-and-Poverty-in-OECD-Regions.pdf
      3. Türkiye İstatistik Kurumu, Hanehalkı İşgücü İstatistikleri, Eylül 2013. (2013, January 16). Retrieved December 14, 2014, from http://www.tuik.gov.tr/PreHaberBultenleri.do?id=13651
      4. Türkiye İstatistik Kurumu, Hanehalkı İşgücü İstatistikleri, Ocak 2013. (2013, April 15). Retrieved December 14, 2014, from http://www.tuik.gov.tr/PreHaberBultenleri.do?id=13483
      5. Social and welfare issues – OECD. (2014, June 19). Retrieved December 10, 2014, from http://www.oecd.org/social/income-distribution-database.htm
      6. Compare your country – Income distribution and poverty. (n.d.). Retrieved December 14, 2014, from http://www.compareyourcountry.org/inequality?cr=oecd&lg=en&page=0
      7. Türkiye İstatistik Kurumu, Hanehalkı İşgücü İstatistikleri, 2013. (2014, March 6). Retrieved December 11, 2014, from http://www.tuik.gov.tr/PreHaberBultenleri.do?id=16015
      8. HANEHALKI İŞGÜCÜ ARAŞTIRMASI 2010 ŞUBAT DÖNEMİ SONUÇLARI (Ocak, Şubat, Mart 2010). (2010, May 17). Retrieved December 11, 2014.
      9. Insights from income distribution and poverty in OECD regions. (2014, July 1). Retrieved December 14, 2014, from http://www.oecd.org/els/soc/OECD2014-Income-Inequality-Update.pdf
      10. Dansuk, E., Özmen, M., & Erdoğan, G. (2008, April 1). Poverty and Social Stratification at the Regional Levels in Turkey. Türk-iş Dergisi.

CMN – FINAL PROJECT

                           ECONOMİC INEQUALITY BETWEEN REGIONS OF TURKEY

I have chosen ”Economic inequality between regions of Turkey” as my topic. I find this topic very interesting because it contains numerical evidences that prove Turkey has a high level of Gini Index which is used to measure the economic status all around the world. It also claims that Turkey is still a developing country. This topic not only considers economic status of Turkey but also it if effected by politics, progress plans of regions and region’s main source of income.Numerical values about Turkey’s economic inequality between regions have many aspects.

First of all, my research will have comparisons of region’s (there are 7 of them: Marmara, Ege, İç Anadolu, Güney Anadolu, Güneydoğu Anadolu, Karadeniz, Doğu Anadolu) income values. I aim to make a conclusion about region’s populations by consideringthese their economic status.

Finally, my research will be grounded to and supported by data of poverty line, general occupation of regions, population, number of poor, regional inequality and immigration.

CMN Project 6

INEQUALİTY IN SOUTH AFRICA

When we think about inequality in South  Africa, maybe the firs thing that comes to our mind is racism. Racism used to be a clasification of people, by deviding and judging them according to their skin colors. Imagine a society which devided in two; ‘’whites and blacks’’. Whites are superriour to blacks just because they have lighter skin and due to the belief that white people have more abilities or qualities.(1) The discrimination was even supported and was legal because of  brutal and restrictive racial regime called apartheid. Apartheid lasted between 1948-1994, during the gouvernement of  National Party with the idea of extending ‘’political and economic control of South Africa by the white minority.’’ (2)  Discrimination based on racism engaged to a new level with apartheid and  played a huge role in South African society.

Gini Index and Inequality

Gini index also known as ‘’the Gini coefficient is a measure of statistical dispersion intended to represent the income distribution of a nation’s residents.’’ Gini index is used to measure inequality by using  frequency distribution such as levels of income. If the gini coefficient is 0(zero) then it’s a perfect equality where everyone’s income is the same. If it is %100 (or 1), it means that the inequality is at a maximum rate. (3) (4)

Table: http://geocurrents.info/wp-content/uploads/2011/05/Figure-9.3.png

As it can be seen in the table, in 1975 that lowest rates of the Gini coefficient belong to white population. This means that white section of the society has a greater chance to get a well-payed jobs and have a constant income. According to apartheid, black Africans had a strict rules of getting a job; the gouvernement limited job oppurtinities to only low-rated jobs. As consequence, black Africans didn’t have a chance to be well-payed, they have the highest gini index in 1975.

Nelson Mandela and Post-apartheid South Africa

Nelson Mandela joined the African National Congress(ANC) in 1944. He was strongly agains apartheid; he became a symbol of anti-apartheid movement. He stood against  a  South  Africa which is ‘’white-ruled British dominion’’ and represented  republic and ‘’it’s majority –black population’’.  In 1994, after the apartheid he was elected President of  South Africa. (7)

Data:  http://cdn.static-economist.com/sites/default/files/imagecache/original-size/images/2013/12/blogs/graphic-detail/20130713_gdc865.png

As we can see through the data, South Africa had the most inequal Gini index between 1960-1985 just after the arrestments where ANC was banned. The lowest Gini index was when apartheid ends due to the limitations of getting a job was demolished. As Mandela steped down as president in 1999, the Gini coefficient started to grow, so does the economic status of people from different races. It is remarquable that even if black population has the biggest percentage through time, yet they have always gained less then others.
Resources

CMN PROJECT 4

In a scientific research the thesis may be the heart but, references are the neural system. References cannot be evitable in order to have a strong and valuable research. References are important in a scientific research because they are the proof that the research is trustable, and the research has a goal to proof it’s ideas.

The first reason why references has a huge impact on a scientific research is that they make the research paper trustworthy. As we all read a research, to believe in it’s ideas and to appreciate it’s value, we need references. References show that the author can use other’s ideas in order to support his or her own. This is an important process which should be included to a scientific research. Also, references show how deeply the arguments were supported. As the arguments are supported with given examples, readers tend to visualize and make connections out of them so that they believe the reseach is trustable.

Another reason why references are important for a scientific research is that they prove the research’s ideas. References are a great symbol of showing variety which is important to prove that the given information is reliable. Variety is a must in every scientific reseach in order to be sure that the conclusion or the idea is correct. As making references in a scientific research author proves that the ideas and the inferences of the research is seen in many times and in many different ways. In this stream, reader gains the ideas more powerfully.

In conclusion, references are indispensable to a scientific research in order to prove that the research has a variety that can be trustable, and that the reseach tends to prove it’s ideas. We should point out that references aren’t only indispensable but also a must for a scientific research to avoide plagiarism. Plagiarism is to use someone else’s ideas or to make quotations without giving references. It’s a serious crime which is basically equal to robbery; you steal ideas, opinions.

Indiana University Confirmation Certificate.zip

CMN THIRD PROJECT

                                             CMN THIRD ASSIGNMENT

   According to my experiences from last week’s assignment, I started with reading the articles with a normal regard so that the articles seemed written with a serious language supported by many numerical evidences. Afterwards as I read them carefully, I figured out many unclear statements and contradictory numerical values.

I would like to start with the article titled “The two-baby family makes a comeback” which is published on 14 July 2011, in the newspaper called Daily Mail. It is obvious that this article contains a lot of various numerical values in order to support their ideas but it also has many inconsistencies. I will talk about these by categorizing them in two groups.

A) Mothers

To begin with, the article says that “mothers now have an average of precisely 2.0 children”. It means that the number of mothers is double of the children. As the article continues, it isn’t mentioned in some parts of the England, a mother may choose to have more children than a woman in the city (high educated, working etc.), so that this average isn’t always true for everyone. The socio-economic status of the parents has a huge impact on deciding how many children they want to have.

Also, the article claims in the title ‘’two-baby family makes a comeback’’. It also contains the numerical values of unmarried woman’s children which is half of the born rates. It seems that the article ignores the fact of children who were born outside marriage build the half of the total born-rate as it announces ‘’nuclear family is still to make a comeback’’. In contrast, this means that half of the mothers prefer not to be married and not to form a ‘’two-baby family’’, neither a ‘’nuclear family’’. It’s an amount which cannot be passed over and be generalized to support their argument.

B) Immigration
Another inconsistency that we can see in the article is in manner of the immigration. It is said in the article that (%25) “a quarter of the births in England and Wales last year (2010) were to mothers who were themselves born abroad” and it is to support their claim which is “birthrates have been driven up by increase in the numbers of foreign-born women with above average fertility”. As it continues, the article says that immigrant women are “more likely to be of childbearing age than the population as a whole”. It doesn’t seem to be right since only 1 in 4 woman of the ‘whole population’ is immigrants and it isn’t reliable since not every woman with a suitable age for childbearing is immigrating to have children. Therefore, contrary as the article states, one of the main reasons for birth rate augmentation cannot be the effect of only immigrants.

In conclusion, this article is obviously written by an exact point of view which is clearly against childbearing out of marriage and immigration. Numerical values were used to somehow support these ideas, but with an attentive reading it is easy to see the numbers weren’t used correctly or compatibly.

Secondly, I will talk about the article titled ‘’How family meals can stop eating disorders’’, published in 14 July 2011, in the newspaper called Daily Mail. The first thing about the article is surely it seems to be short and to the point. However, it contains several numerical values and percentages which were used incompatibly.

First of all, the article declares two percentages; ‘’They were also 24 per cent more likely to… have healthy eating habits than those who didn’t share three meals with their families’’ and ‘’teens who eat at least five meals a week with their families are 35 per cent less likely to be ‘disordered eaters’’. These numerical statements don’t show the same percentage of how effective is eating one meal with family per week. First one declares it as %8 while the second one declares it as %7.
Another untrue statement is that the article talks about 17 studies on eating patterns and nutrition involving ‘almost’ 200.000 children and teenagers. It doesn’t clarify which age group (which is actually 2-17) was involved in the study and what did this study really pertained. The exact amount of children and teenager who were in the study was actually 182.000. The article ignores about 18.000 subjects which is a high number that couldn’t be unmentioned in order to reflect the true numerical value.

The last thing I would like to point out is how the article defines disordered eating. It is said in the article that ‘’smoking to keep a lid on weight’’ is also a sign of eating disorders. Actually, this action doesn’t define an eating disorder at all. The article is far from reflecting the real definition and causes of disordered eating. In addition, it isn’t even mentioned once eating excessive amounts of food, psychological effects of eating disorders, and unhealthy nutrition habits in schools or even in families.

To conclude, the article tries to fix the idea of eating with family is a great way to control children and teenagers. It tries to use the numerical facts and percentages as they are proof of this idea by reconstituting the data.

I really enjoyed reading the articles and doing the research on these topics. Since I really understood the methodology of how to detect false usage of numbers and how they were used to manipulate the reader’s ideas. I look forward to write more reports and get better at criticizing what I read in my personal life.

Sources for the first article:

http://www.theguardian.com/society/2009/may/21/birth-rate-increase

http://www.ons.gov.uk/ons/dcp171766_350433.pdf

http://www.ons.gov.uk/ons/rel/fertility-analysis/childbearing-of-uk-and-non-uk-born-women-living-in-the-uk/2011-census-data/sty-mothers-country-of-birth.html

Sources for the second article:
http://pediatrics.aappublications.org/content/127/6/e1565.full

http://web.extension.illinois.edu/state/newsdetail.cfm?NewsID=26142

http://news.illinois.edu/news/11/0620mealtime_BarbaraFiese.html

http://www.nedic.ca/know-facts/definitions

CMN Second Project

CMN SECOND PROJECT

As a group, we were already aware of the spreading and increasing disease cancer. As we started to do research about the topic of this assignment, we had a better chance to get a closer look to the causes and effects of cancer. We realized how quickly it spreads and how common it is.

When we read the article called “One in four Britons will get cancer” that was on Daily Mail, July 14, 2011, we caught many incomplete and missing informations. These mistakes are such as;

-Untrue assumptions

-Contradictory expressions

-Numerical errors

-Unmentioned sources

-Undetermined research methods

-Too many exaggerations and generalizations

-Unclear statements

First of all, we started with the statement mentioned in the title “One in four Britons will get cancer”. 62.649.014 is the population of England in 2011. According to title 15.662.253 people will get cancer. As the article declares afterwards “ There are currently two million people in Britain with the ilness and this is expected to double within the next 20 years”. According to this statement if it continues to double every 20 years, it will reach appromixely to 15.662.253 after 60 years.

Secondly, in the article it is given that “some” %64 eventually die from the cancer but as we made a research about cancer survivors we found out that there are %50 survivors and this is still increasing. Also the word “some” is an unclear statement and cannot be used when giving a specific percentage.

Furthermore, the article announces that the reason of the cancer is “lifestyle factors such as obesity, excessive drinking and smoking”. However, according to our researches genetic tendency for the cancer has the main role in getting this disease. This article doesn’t even mention this reason once. If the genetic code has a tendency for cancer, outer factors trigger the risk of this disease.

Another unclear statement is that “ it (cancer) is also partly a result of people living longer”. It’s a fact that with getting older, every disease has more risk to be developed. This cannot support the article’s thesis. It’s an unnecessary information, exaggeration and generalization.

The other reason why we can’t rely on the article’s arguments is that it doesn’t name the research’s method. For example, the AMP method calculates the percentage of the cancer with counting all the diagnoses but it also contains the same person’s diognoses which may also be more than once. As a result, this method does not give us the number of people who suffer from cancer, it gives us the percentage of diognoses compared to population. So, since it isn’t given the research method we can’t accept it as a clear support.

In conclusion, we think that an article about something serious should have been more accurate and clear. It strains the truths about the sickness, its causes and the percentages.

As a group, we chose to communicate from Whatsapp and formed a gruop called “Project CMN”. We scheculed appointment in ÇSM three times. First, we read and discussed about the article. Then, we did a research from Internet about the population, percentages and causes of cancer. Finally, we wrote our report by gathering the information that we found. The avantages of working face to face are:

-Better communication

-Time saving

-Better discussion environment

-Better information sharing

For me, this assigment pointed out a very important subject; misinformation published in newspapers. It is a common problem that we all suffer from it. In every country, media anounces their articles with exagerations to control and to manipulate the people. As concious individuals, we all must be aware of what we read cannot be true. We should think before we believe everything we read. I had a great time with my group members as we studied together.

– Selen Demircioğlu

Qualified information is a really important issue that everyone should be aware. As we read the article, we found so much mistakes, uncompleted, untrue or unclear statements. We realized that we shouldn’t trust everything we read. We researched about the informations that the article gave; it was clear that the informations were distorted to attract more attention. Doing this research with a group helped us find the mistakes easily by doing brainstorming. Also, we really enjoyed this work.

-Deniz Ersoy

This assignment was really hard to deal with because it was very complicated and so many mistakes were made in the article. It took long time to point out them and research and find the proves. I realised one more that we should not trust everything we read or hear. Plus we shouldn’t believe an article just because it’s on a popular news or websites. An article should have prove so that people can trust and believe in the information that is given. Above all, I really enjoyed doing this assignment with my group members.
-Bilge Tuzen

Sources:

http://www.theguardian.com/news/datablog/2009/oct/21/uk-population-data-ons

http://en.wikipedia.org/wiki/Demography_of_the_United_Kingdom#Age_structure

http://www.macmillan.org.uk/Cancerinformation/Causesriskfactors/Healthandlifestyle.aspx

http://www.theworkfoundation.com/blog/600/Managing-Cancer-in-the-Workplace

http://www.cancerresearchuk.org/cancer-info/cancerstats/incidence/uk-cancer-incidence-statistics

http://www.cancerresearchuk.org/cancer-info/cancerstats/survival/

http://www.cancerresearchuk.org/cancer-info/cancerstats/incidence/risk/

Ishango Bone and Lebombo Bone

Numbers have been used since such a long time regarding that calculation of the field yard in Mesopotamia or solar calendar in Ancient Egypt. These computations are basically for facilitate human life and understand the natural events. However these aren’t the most ancient proofs which show that people used numbers for such a long time. Recent researches indicated that the Ishango Bone and the Lebombo Bone are even older and the very first tools for calculating. But the question we discussed with my group members in class is mainly about the reasons why these bones are used.

The first reason why the Ishango Bone may have been used is that it helps to understand some basic mathematical calculations. Calculating is one of the most ancient ways that people use to facilitate their lives.  As we all know, in African culture they don’t have personal belongings but they have a system based on sharing. Ishango Bone has a principle constructed on division and multiplication.   These calculations may have been useful to devise equally any kind of substances (food, hunting tools etc.) they had. That’s the reason why with my group we found this thesis possible.

Another reason why the Ishango Bone and the Lebombo Bone could be used is that to count and track the days. We have always needed to understand natural events due to their effect on human life, so, with calculating monthly cycle woman may have also understood about their menstrual cycles. As a result, by tracking the calendar that they created, African woman could successfully understand their natural functions of their bodies. It’s a fact that African communities are matriarchal because they believe that the life comes from a woman’s body. This consideration shows that the fertility of a woman is very important in such African populations so that me and my group strongly believe that this is the main reason why these bones were used.

In conclusion, there are two aspects about function of the Ishango and the Lebombo bones. In the class discussion with my group we have found the second one more efficient. Other than the reason why the bones were uses, we have also discussed about the items which we use today will misunderstood as well. We think that kitchen appliances will be the most difficult tools to predict the function. Who knows; in 20.000 years maybe all of our ‘‘indispensable’’ tools will be all forgotten, but surely the numbers will still be used.