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Tom W. Smith, NORC/University of Chicago

The General Social Survey and the International Social Survey Program: Monitoring America across Time and in Comparative Perspective October , 2011. Tom W. Smith, NORC/University of Chicago. Table 1-1. Overall Design Features. Table 1-2. Overall Design Features.

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Tom W. Smith, NORC/University of Chicago

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  1. The General Social Survey and the International Social Survey Program: Monitoring America across Time and in Comparative PerspectiveOctober, 2011 Tom W. Smith, NORC/University of Chicago

  2. Table 1-1. Overall Design Features

  3. Table 1-2. Overall Design Features

  4. Table 1-3. Overall Design Features

  5. Table 1-4. Overall Design Features

  6. Table 2-1. Topical Modules

  7. Table 2-2. Topical Modules

  8. Table 2-3. Topical Modules

  9. ARCTIC OCEAN ARCTIC OCEAN Ust-Olenek Khatanga Barrow Volochanka GREENLAND Alta Dudinka Antipayuta Belaja Gora Norilsk Murmansk Kiruna Batagay Vorkuta Igarka Arctic Circle Arctic Circle Fort Yukon SWEDEN Lulea Port Radium RUSSIA ICELAND Fairbanks Skelleftea Nome Baker Lake Sangar Archangelsk Nuuk FINLAND Ostersund Reykjavik Vaasa Rankin Inlet Torshavn Jakutsk Mirnyj NORWAY Anchorage Syktyvkar Nizhnevartovsk Helsinki Cordova Oslo Magadan Stockholm St. Petersburg Tallinn Fort Chipewyan Churchill Kirov ESTONIA Vologda Juneau Perm Bodaybo Inukjuak Novgorod Jaroslavl Riga Sverdlovsk Fort McMurray Rostov DENMARK Gorkiy LATVIA Bear Lake Bratsk Krasnojarsk Izevsk Copenhagen Moscow Dawson Creek Thompson Kazan LITHUANIA Chelyabinsk Grande Prairie Kaunas Sunderland Ufa Flin Flon Omsk Minsk Novosibirsk Prince Rupert Prince George Dublin Tol Yatti Gdansk Prince Albert Unalaska NETH. Orol U. K. Berlin Kuybyshev BELARUS Labrador City POLAND IRELAND Red Deer Rudnyy Petropavlovsk-Kamchatskij London Atbassar Voronez Astana Saskatoon Saratov Irkutsk Warsaw CANADA Calgary Ulan Ude Cork GERMANY Kamloops Kiev Moosonee Krakow BELGIUM Lviv Swift Current LUX. Aktyubinsk CZECH Vancouver Brandon UKRAINE Qaraghandy Volgograd Paris Khabarovsk KAZAKHSTAN Amos Timmins SLOVAKIA Ulaanbaatar Hovd Williston Grand Forks Spokane Qiqihar MOLDOVA Juzno Sachalinsk Balqash Aralsk MONGOLIA Frunze Seattle Nantes Altay Butte ROMANIA Duluth Harbin Karamay Ottawa Montreal Jixi ITALY FRANCE Minneapolis Bucharest Portland Krasnodar Alma Changchun Urumqi Jilin Dalandzadagad Toulouse Bayonne Constanta Ata Sapporo Bishkek MilWawkee Detroit Twin Falls UZBEKISTAN Fuxin Buffalo Korla Valladolid Boston GEORGIA Scottsbluff Hami Chicago Benxi KYRGYZSTAN Porto Madrid Rome Baotou Omaha Ankara AZERBAIJAN Beijing NORTH KOREA Barcelona ARMENIA Tashkent Yumen Provo PORTUGAL New York Naples Reno Denver Baltimore Kashi TURKMENISTAN Pyongyang Kansas City GREECE Philadelphia SPAIN TURKEY TAJIKISTAN Izmir Qiemo Yinchuan Ashgabat U. S. A. Lisbon Seoul Washington D. C. Ponta Delgada Oakland Dalian St. Louis Sevilla Hotan Sendai Adana San Francisco Taiyuan Xining Athens Golmud PACIFIC Norfolk Qingdao Tunis SOUTH KOREA Algiers Gibraltar PACIFIC Tehran Albuquerque Charlotte Nicosia Las Vegas Memphis Lanzhou SYRIA CHINA Kaifeng Kabul TUNISIA CYPRUS Bakhtaran Tokyo Rabat Atlanta Casablanca LEBANON ATLANTIC Xian Tripoli Los Angeles Dallas Esfahan JAPAN Baghdad Tucson Birmingham MOROCCO Islamabad ISRAEL AFGHANISTAN Ouargla San Diego Mianyang Hefei IRAQ IRAN Basra Shanghai Jacksonville Houston Chengdu JORDAN Canary Islands ALGERIA New Delhi Multan New Orleans Cairo Huangshi Ningbo Shiraz Zigong Yueyang NEPAL KUWAIT PAKISTAN Sabhah Agra Tampa Jaipur Reggane Wenzhou BHUTAN Dukou EGYPT Fuzhou WESTERN THE BAHAMAS Guiyang LIBYA Riyadh Taipei QATAR Allahabad MEXICO SAHARA Xiamen Dhaka Tropic of Cancer Havana Tropic of Cancer Djanet (occupied by Morocco) Ahmadabad Shantou U. A. E. Nanning Aswan Muscat Al Jawf TAIWAN Kolkata (Calcutta) Makkah (Mecca) Surat Ulhasnagar Hong Kong CUBA MYANMAR SAUDI ARABIA Nagpur Mexico City Hanoi DOM. REP. MAURITANIA LAOS Araouane BANGLADESH Bilma JAMAICA Mumbai OMAN (Bombay) MALI Rangoon Pune Nouakchott NIGER OCEAN HAITI Vientiane BELIZE YEMEN Khartoum ERITREA HONDURAS VIETNAM THAILAND Asmara CHAD Dakar Bangkok Sanaa Niamey INDIA Manila Bamako GUATEMALA SUDAN PHILIPPINES Chennai (Madras) CAMBODIA NICARAGUA EL SALVADOR Phnom Penh DJIBOUTI NIGERIA NÕDjamena GUINEA BENIN Abuja Addis Abbaba GHANA SOMALIA Ho Chi Minh City Caracas Conakry Cochin IVORY TOGO COSTA RICA Waw Freetown SRI LANKA VENEZUELA Georgetown COAST Porto Novo CENTRAL AFRICAN ETHIOPIA PANAMA Paramaribo Colombo REPUBLIC Davao Monrovia BRUNEI Bogota CAMEROON Lome Accra Kuala Lumpur Bangui Abidjan Malabo INDIAN MALAYSIA Yaounde UGANDA EQUATORIAL GUINEA COLOMBIA KENYA Mogadishu SAO TOME & PRINCIPE Equator Equator CONGO Equator Kampala Quito ECUADOR Libreville Singapore Nairobi Sao Tome DEM. REP. GABON OF CONGO RWANDA Belem Manaus Brazzaville Fortaleza BURUNDI Talara Jakarta Kinshasa PAPUA ANGOLA Sao Goncalo TANZANIA PERU Kananga INDONESIA NEW GUINEA Dar es Salaam Dili Recife Cachimbo Porto Velho Trujillo OCEAN Luanda EAST TIMOR OCEAN Port Moresby Likasi Lima COMOROS Barreiras BRAZIL Huambo BOLIVIA Salvador ZAMBIA MALAWI ANGOLA La Paz Lusaka Cuiaba Cairns FIJI Goiania Sucre Harare Antananarivo Broome Tennant Creek Belo Horizonte ZIMBABWE NAMIBIA Port Hedland Mackay Windhoek Learmonth Tropic of Capricorn Tropic of Capricorn Tropic of Capricorn MADAGASCAR Campinas BOTSWANA Alice Springs NEW CALEDONIA Gaborone Walvis Bay Rio De Janeiro Antofagasta Sao Paulo Pretoria Curitiba Asuncion Carnarvon Tolanaro AUSTRALIA Maputo CHILE Mbabane Brisbane Luederitz Bloemfontein SWAZILAND ARGENTINA Geraldton Bourke Porto Alegre Cook Kalgoorlie SOUTH AFRICA LESOTHO Rosario OCEAN Umtata Perth Santiago Adelaide Sydney Cape Town Port Elizabeth Buenos Aires Montevideo Canberra Concepcion Melbourne Auckland Neuquen Valdivia Wellington NEW ZEALAND Comodoro Rivadavia Dunedin Port Stanley Red=ISSP, Black=Former ISSP 1000 Km Scale at Equator

  10. Table 3-1. ISSP Modules

  11. Table 3-2. ISSP Modules

  12. Table 3-3. ISSP Modules

  13. Table 3-4. ISSP Modules

  14. Table 4. GSS Reinterviews

  15. Table 5. Auxiliary/Follow-Up Studies

  16. Table 6Most Frequently Used Data Sets in Leading Sociology Journals, 1991-2010 • Census/CPS/ACS, etc. 281 • GSS/ISSP 248 • National Longitudinal Survey of Youth 63 • Adolescent Health 53 • Panel Survey of Income Dynamics 48 • National Educational Longitudinal Survey 36 • National Survey of Families and Households 36 • National Election Studies 18 • High School and Beyond 16 • World Values Survey 16 • Based on American Journal of Sociology, American Sociological Review, and Social Forces.

  17. Table 7 Rotating, Three-Wave Panel/Cross Section Design Realized and Projected Sample Sizes, 2006-2014 Panels Year 200620082010201220142016 Panel 2006 200015361276--------------- 2008 -----20231581(1312) ---------- 2010 ----------2044(1533) (1226) ----- 2012 ----- ----------(2000) (1500) (1200) 2014 --------------------(2000) (1500) Numbers in parentheses (…) are projected future targets.

  18. Table 1Cohort Differences Regarding Abortion Attitudes • Before 1904- 1914- 1924- 1934- 1944- 1954- 1964- 1974- 1984+ • 1903 1913 1923 1933 1943 1953 1963 1973 1983 • % for abortion for • rape victim 73.7 77.9 77.4 7 8.8 76.5 80.7 79.8 81.2 77.0 73.8 • % for abortion for • birth defect 68.9 75.6 77.1 79.1 77.6 80.7 78.7 76.6 70.1 66.0 • % for abortion for • mother’s health 78.8 83.4 85.3 86.9 87.1 89.8 89.1 88.5 84.9 72.7 • % for abortion for • unmarried mother 35.4 38.0 40.5 41.1 41.6 48.1 43.6 39.8 33.1 36.0 • % for abortion for • low-income mother 40.1 43.3 43.3 43.5 43.4 50.7 46.2 44.8 40.2 37.4 • % for abortion for not • having more kids 29.3 35.5 37.5 39.8 40.9 48.5 44.3 42.0 36.3 32.0 • % for abortion for • any reason 25.1 28.7 31.6 33.0 36.0 43.1 41.4 41.3 36.2 32.0 • Source: GSS 1972-2006 • Please tell me whether or not you think it should be possible for a pregnant woman to obtain a legal abortion . . . • READ EACH STATEMENT, AND CIRCLE ONE CODE FOR EACH. • a. If there is a strong chance of serious defect in the baby? • b. If she is married and does not want any more children? • c. If the woman’s own health is seriously endangered by the pregnancy? • d. If the family has a very low income and cannot afford any more children? • e. If she became pregnant as a result of rape? • f. If she is not married and does not want to marry the man? • g. If the woman wants it for any reason?

  19. Questions Wordings Domain-Specific National Pride How proud are you of COUNTRY in each of the following? Very Proud/Somewhat Proud/Not Very Proud/Not at All Proud 1. The way democracy works 2. Its political influence in the world 3. COUNTRY’S economic achievement 4. Its social security system 5. Its scientific and technological achievements 6. Its achievements in sports 7. Its achievement in the arts and literature 8. COUNTRY’S armed forces 9. Its history 10. Its fair and equal treatment of all groups in society

  20. Overall Rank of Countries on Domain-Specific National Pride

  21. National Pride Rankings Across Ten Domains

  22. National Pride Rankings Across Ten Domains

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