Obecnie niewiele miejsca poświęca się w opracowaniach historycznoliterackich nurtowi Nowego Dziennikarstwa. Szczególnie w Polsce czytelnik lub badacz rzadko ma okazję dostrzec to zjawisko. W Stanach Zjednoczonych w latach sześćdziesiątych i siedemdziesiątych cieszyło się ono dużą popularnością i wzbudzało ogromne zainteresowanie. Wielu Nowych Dziennikarzy zdobyło sławę i miano celebrytów. W Polsce autorzy reprezentujący owe dziennikarstwo są mało znani, a ich twórczość tylko sporadycznie pojawia się w księgarniach. Powodem takiej sytuacji może być obawa tłumaczy i wydawców przed ograniczeniami związanymi z nieznajomością kontekstu kulturowego i polityczno-historycznego tekstów. Uważam, że jeśli taki jest powód niewielkiej popularności tego nurtu w Polsce, to należałoby zachęcić do sięgnięcia po lekturę dzieł takich kronikarzy jak Tom Wolfe czy Hunter Thompson. Bowiem twórczość autorów Nowego Dziennikarstwa dostarcza czytelnikowi ogromnej wiedzy o sytuacji politycznej, społecznej i kulturowej Ameryki drugiej połowy XX wieku, wyjaśnia przedstawione wydarzenia i obszernie je komentuje. Teksty Nowych Dziennikarzy wpisują się także w dyskusję nad tym jaką rolę tekst dziennikarski odgrywa w dostarczaniu wiedzy o świecie i interpretowaniu rzeczywistości. W mojej książce pragnę dowieść, że teksty z nurtu Nowego Dziennikarstwa są szczególnie ważnym źródłem wiedzy o kontrkulturze lat sześćdziesiątych. Fakt ten jest często ignorowany w badaniach kontrkultury, które skupiają się najczęściej tylko na analizie dokumentów historycznych i socjologicznych a zapominają o, w równej mierze ważnych, literackich reprezentacjach epoki lat sześćdziesiątych. Lata sześćdziesiąte w Stanach Zjednoczonych były erą burzliwych przemian społecznych, masowych rozruchów, antywietnamskich protestów, rewolucji seksualnej, zamachów politycznych, strajków studenckich, demonstracji, które wstrząsały Amerykanami. Nie byli oni w stanie zrozumieć tempa przemian oraz wydarzeń, których byli świadkami. W tym okresie zamordowano prezydenta Stanów Zjednoczonych, Johna Kennedy'ego, zastrzelono Martina Luthera Kinga, represjonowano walczącą o swobody życiowe część społeczności amerykańskiej. Codziennością stało się uczestniczenie w masowych pogrzebach ciał przywożonych z Wietnamu żołnierzy. Dziennikarze i reportażyści próbowali wytłumaczyć ludziom skomplikowaną naturę otaczającej ich rzeczywistości. By sytuację unaocznić, przedstawić zrozumiale i wyczerpująco musieli zastosować nowe sposoby i metody obrazowania i przedstawiania świata. Zmienili dotychczasowe środki wyrazu, użyli narracji, monologu wewnętrznego, dialogu, bogatych opisów świata, nadali koloryt widzianym obrazom. Tak powstało jedno z ciekawszych zjawisk literackich tamtej epoki – Nowe Dziennikarstwo, którego twórcy odpowiadali na zapotrzebowania społeczne analizując i komentując ważne wydarzenia polityczne i kulturalne Ameryki. Rysując skomplikowaną rzeczywistość Nowi Dziennikarze stworzyli reportażowo-literacki styl, zawierający socjologiczne i historyczne walory. Żywiołowo relacjonowali także rozwijającą się kulturę popularną, byli głównymi kronikarzami kontrkultury i czasów hippisowskich. Przede wszystkim jednak Nowe Dziennikarstwo i jego twórcy okazali się wspaniałymi charakteryzatorami jednostek. Poprzez opis zachowań postaci, ich sposobu mówienia, stylu ubierania, miejsc zamieszkania, charakteru wykonywanych przez nie prac dawali obraz ówczesnego społeczeństwa kontestującego. Celem niniejszej książki jest analiza wybranych tekstów Nowego Dziennikarstwa, która pozwala lepiej zrozumieć kontrkulturę i obyczaje Ameryki lat sześćdziesiątych, scharakteryzować ówczesną sytuację, oraz umożliwić dostrzeżenie wszystkiego w jaskrawych i wyraźnych kolorach. Kluczem do analizy stała się teoria nowego historyzmu, który przywrócił dziełom literackim kontekst historyczny, nie traktując tekstu jako autonomicznego tworu, a osadzając go w kontekście kulturowym. Literatura bowiem przekazuje społeczne, polityczne i kulturowe nastroje, ukazując ducha danej epoki. Nowi historycyści postrzegają ją jako źródło historyczne, odzwierciedlające realną rzeczywistość. Chcąc przedstawić nieodzowny kontekst do analizy kontrkultury, próbuję w rozdziale pierwszym przedstawić tło historyczne buntu i udział w nim prekursorów – hipsterów i bitników. Dalej zmierzam do przedstawienia wybuchu rebelii hippisowskiej w latach sześćdziesiątych, opisuję również społeczne i kulturowe przyczyny powstania kontrkultury, analizuję wydarzenia, które doprowadziły do upadku ruchu hippisowskiego. W rozdziale drugim skupiam się na okolicznościach narodzin i charakterystyce Nowego Dziennikarstwa, przedstawiam jego prekursorów, ich twórczość oraz głosy krytyki. Wskazuję też na fakt podniesienia rangi dziennikarstwa i przyczynienia się do jego rozwoju i rozpowszechnienia. W rozdziale trzecim zajmuję się genezą wymienionych niżej tekstów i przedstawiam sylwetki ich autorów. W drugiej części książki analizuję poszczególne powieści i artykuły prasowe Nowego Dziennikarstwa, które w całości skupiają się na ruchu hippisowskim i jego upadku. Analiza obejmuje powieści: Próbę kwasu w elektrycznej oranżadzie (1968) Toma Wolfa, Lęk i odrazę w Las Vegas (1971) Huntera Thompsona, esej Joan Didion Slouching Towards Bethlehem (1968), artykuły Richarda Goldsteina: Psychedelic Psell (1967), The Catcher In the Haight (1967), Love: A Groovy Idea While He Lasted (1967), San Francisco Bray (1967) oraz artykuły Huntera Thompsona: Why Boys Will Be Girls (1967), The 'Hashbury' Is the Capital of the Hippies (1967), The Hippies (1967). W książce wykorzystuję również do analizy fragmenty Hell's Angels. Anioły piekieł (1966) Huntera Thompsona, The Armies of the Night (1968) Normana Mailera, Loose Change (1977) Sary Davidson oraz We Are The People Our Parents Warned Us Against (1968) Nicholasa Von Hoffmana. Głównymi kryteriami wyboru tekstów były kontrkulturowe treści w nich zawarte oraz przynależność ich autorów do nurtu Nowego Dziennikarstwa. Analiza wspomnianych tekstów pozwala na scalenie i szerokie zobrazowanie integralnych elementów kontrkultury. W mojej książce opisuję rolę kontrkulturowych liderów, którzy w ogromnej mierze przyczynili się do rozszerzenia ruchu hippisowskiego i propagowania idei kontestacyjnych. Wskazuję na używanie środków poszerzających świadomość jako nieodłączną część buntu lat sześćdziesiątych. Opisuję hippisowskie komuny, życie w atmosferze wolnej miłości i rewolucji seksualnej. Analizuję komuny jako alternatywny sposób życia oraz jako formy protestu przeciw establishmentowi. Ukazuję rolę muzyki, tekstów piosenek, wydarzeń muzycznych i muzycznych idoli w czasach kontrkultury. W dalszej części książki omawiam czynniki, które w późnych latach sześćdziesiątych doprowadziły do upadku kontrkultury. Analiza kończy się zobrazowaniem komercjalizacji ruchu hippisowskiego, schyłku dekady lat sześćdziesiątych, upadku kontrkultury i koncepcji "American Dream". Śmiem twierdzić, że teksty, które wyszły spod pióra Nowych Dziennikarzy nie są dziś jedynie kulturowym artefaktem. Są bogatym źródłem wiedzy na temat kontrkultury lat sześćdziesiątych oraz częścią dziejów Stanów Zjednoczonych. Przedziwne i często zdumiewające wydarzenia, opisywane przez autorów, mogą stanowić źródło silnych i głębokich przemyśleń. Są jednocześnie jak ożywczy wiatr, który otwiera okiennice okna i pozwala na szersze, wyraźniejsze widzenie świata i jego spraw, oglądanych dotychczas tylko przez szparę owych okiennic. Szeroko otwarte okno jest metaforą odbierania świata widzianego nie wyłącznie przez "szkiełko i oko", ale wzbogaconego uczuciami Nowych Dziennikarzy, ich świeżym spojrzeniem, ich młodymi opiniami, interpretacją, dziennikarską swobodą i swadą. Należy podkreślić, że teksty Nowych Dziennikarzy są ważną i nierozerwalną częścią historii, stanowią dokumenty, które powinny być traktowane na równi z tekstami czysto literackimi, historycznymi i socjologicznymi. 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The Complete Guide to the Legendary Trip of Ken Kesey and the Merry Pranksters and the Birth of the Counterculture, New York: Thunder's Mouth Press, 1990, xv-xvi. ; Torgoff, Martin. Can't Find My Way Home: America in the Great Stoned Age 1945-2000, New York: Simon & Schuster Paperbacks, 2005. ; Tytell, John. Naked Angels. The Lives and Literature of the Beat Generation, New York: McGraw-Hill, 1976. ; Usher Henderson, Katherine. Joan Didion, New York: Ungar, 1981. ; Van Meter, Jonathan. "When Everything Changes", New York Books, October 7, 2005. article on-line available from: http://nymag.com/nymetro/arts/books/14633/. Accessed: Dec. 7, 2010. ; Watson, Steven. The Birth of the Beat Generation, New York: Pantheon Books, 1998. ; Weber, Ronald. The Literature of Fact: Literary Nonfiction in American Writing, Athens, Ohio: Ohio University Press, 1980. ; Weinberg, Arthur and Lila. The Muckrakers, Urbana: University of Illinois Press, 2001. ; Weingarten, Marc. The Gang That Wouldn't Write Straight, New York: Three Rivers Press, 2005. ; Whelan, Brent. "Furthur: Reflections on Counter-Culture and the Postmodern", Cultural Critique, Number 11, Winter 1988-89, 63-86. ; Whitmer, Peter O. When the Going Gets Weird: The Twisted Life and Times of Hunter S. Thompson: a very unauthorized biography, New York: Hyperion, 1993. ; Whitmer, Peter O. and Bruce VanWyngarden. Aquarius Revisited, New York: Macmillan, 1987. ; Willis, Paul E. Profane Culture, London: Routlege & Kegan Paul, 1978. ; Winchell, Mark Royden. "Joan Didion" in James R. Giles and Wanda H. Giles, eds., American Novelists Since World War II: Fifth Series, Detroit: Gale Research, 1996. Accessed: Nov. 29, 2010. ; Wolfe, Tom. The Kandy-Kolored Tangerine-Flake Streamline Baby, London: Picador, 1966. ; Wolfe, Tom. The New Journalism, London: Picador, 1975. ; Yardley, Jonathan. "The Sixties Revival: Echoes from an Empty Decade," Washington Post, July 24, 1987, C2. ; Yablonsky, Lewis. The Hippie Trip, San Jose: toExcel, 2000. ; Yinger, John Milton. "Contraculture and Subculture," American Sociological Review 25(1960), 625-635. ; Zimmerman, Nadya. Counterculture Kaleidoscope: musical and cultural perspectives on late sixties San Francisco, Ann Arbor, Mich.: University of Michigan Press, 2008. ; Żulczyk, Jakub. "W poszukiwaniu amerykańskiego snu", introduction to Hunter S. Thompson, Lęk i odraza w Las Vegas, translated by Marcin Wróbel, Maciej Potulny, Warszawa: Niebieska Studnia, 2008, 257-270. ; Gibney, Alex (director). Gonzo: The Life and Work of Dr. Hunter S. Thompson, USA: Magnolia Home Entertainment, 2008. ; Dylan, Bob. "Mr. Tambourine Man", Bringing It All Back Home, 1965. Lyrics available from: http://www.bobdylan.com/songs/mr-tambourine-man. Accessed: Jan. 3, 2012. ; Jefferson Airplane. "White Rabbit", Surrealistic Pillow, 1967. Lyrics available from: http://www.metrolyrics.com/white-rabbitlyrics-jefferson-airplane.html. Accessed: Jan. 3, 2012. ; Jefferson Airplane. "Let's Get Together", Jefferson Airplane Takes Off, 1966. Lyrics available from: http://www.lyricsfreak.com/ j/jefferson+airplane/lets+get+together_20244570.html. Accessed: Jan. 3, 2012. ; McLean, Don. "American Pie", American Pie, 1971. Lyrics available from: http://www.lyrics007.com/Don%20McLean%20Lyrics/American%20Pie%20Lyrics.html. Accessed: Jan. 3, 2012.
The module was administered as a post-election interview. The resulting data are provided along with voting, demographic, district and macro variables in a single dataset.
CSES Variable List The list of variables is being provided on the CSES Website to help in understanding what content is available from CSES, and to compare the content available in each module.
Themes:
MICRO-LEVEL DATA:
Identification and study administration variables: weighting factors; election type; date of election 1st and 2nd round; study timing (post-election study, pre-election and post-election study, between rounds of majoritarian election); mode of interview; gender of interviewer; date questionnaire administered; primary electoral district of respondent; number of days the interview was conducted after the election; language of questionnaire.
Demography: year and month of birth; gender; education; marital status; union membership; union membership of others in household; business association membership, farmers´ association membership; professional association membership; current employment status; main occupation; socio economic status; employment type - public or private; industrial sector; current employment status, occupation, socio economic status, employment type - public or private, and industrial sector of spouse; household income; number of persons in household; number of children in household under the age of 18; number of children in household under the age of 6; attendance at religious services; religiosity; religious denomination; language usually spoken at home; region of residence; race; ethnicity; rural or urban residence; primary electoral district; country of birth; year arrived in current country.
Survey variables: perception of public expenditure on health, education, unemployment benefits, defense, old-age pensions, business and industry, police and law enforcement, welfare benefits; perception of improving individual standard of living, state of economy, government's action on income inequality; respondent cast a ballot at the current and the previous election; vote choice (presidential, lower house and upper house elections) at the current and the previous election; respondent cast candidate preference vote at the current and the previous election; difference who is in power and who people vote for; sympathy scale for selected parties and political leaders; assessment of parties on the left-right-scale and/or an alternative scale; self-assessment on a left-right-scale and an optional scale; satisfaction with democracy; party identification; intensity of party identification, institutional and personal contact in the electoral campaigning, in person, by mail, phone, text message, email or social networks, institutional contact by whom; political information questions; expected development of household income in the next twelve month; ownership of residence, business or property or farm or livestock, stocks or bonds, savings; likelihood to find another job within the next twelve month; spouse likelihood to find another job within the next twelve month.
DISTRICT-LEVEL DATA: number of seats contested in electoral district; number of candidates; number of party lists; percent vote of different parties; official voter turnout in electoral district.
MACRO-LEVEL DATA: election outcomes by parties in current (lower house/upper house) legislative election; percent of seats in lower house received by parties in current lower house/upper house election; percent of seats in upper house received by parties in current lower house/upper house election; percent of votes received by presidential candidate of parties in current elections; electoral turnout; party of the president and the prime minister before and after the election; number of portfolios held by each party in cabinet, prior to and after the most recent election; size of the cabinet after the most recent election; number of parties participating in election; ideological families of parties; left-right position of parties assigned by experts and alternative dimensions; most salient factors in the election; fairness of the election; formal complaints against national level results; election irregularities reported; scheduled and held date of election; irregularities of election date; extent of election violence and post-election violence; geographic concentration of violence; post-election protest; electoral alliances permitted during the election campaign; existing electoral alliances; requirements for joint party lists; possibility of apparentement and types of apparentement agreements; multi-party endorsements on ballot; votes cast; voting procedure; voting rounds; party lists close, open, or flexible; transferable votes; cumulated votes if more than one can be cast; compulsory voting; party threshold; unit for the threshold; freedom house rating; democracy-autocracy polity IV rating; age of the current regime; regime: type of executive; number of months since last lower house and last presidential election; electoral formula for presidential elections; electoral formula in all electoral tiers (majoritarian, proportional or mixed); for lower and upper houses was coded: number of electoral segments; linked electoral segments; dependent formulae in mixed systems; subtypes of mixed electoral systems; district magnitude (number of members elected from each district); number of secondary and tertiary electoral districts; fused vote; size of the lower house; GDP growth (annual percent); GDP per capita; inflation, GDP Deflator (annual percent); Human development index; total population; total unemployment; TI corruption perception index; international migrant stock and net migration rate; general government final consumption expenditure; public spending on education; health expenditure; military expenditure; central government debt; Gini index; internet users per 100 inhabitants; mobile phone subscriptions per 100 inhabitants; fixed telephone lines per 100 inhabitants; daily newspapers; constitutional federal structure; number of legislative chambers; electoral results data available; effective number of electoral and parliamentary parties.
The module was administered as a post-election interview. The resulting data are provided along with voting, demographic, district and macro variables in a single dataset.
CSES Variable Table The list of variables is being provided on the CSES Website to help in understanding what content is available from CSES, and to compare the content available in each module.
Themes:
MICRO-LEVEL DATA:
Identification and study administration variables: weighting factors; election type; date of election 1st and 2nd round; study timing (post-election study, pre-election and post-election study, between rounds of majoritarian election); mode of interview; gender of interviewer; date questionnaire administered; primary electoral district of respondent; number of days the interview was conducted after the election; language of questionnaire.
Demography: year and month of birth; gender; education; marital status; union membership; union membership of others in household; business association membership, farmers´ association membership; professional association membership; current employment status; main occupation; socio economic status; employment type - public or private; industrial sector; current employment status, occupation, socio economic status, employment type - public or private, and industrial sector of spouse; household income; number of persons in household; number of children in household under the age of 18; number of children in household under the age of 6; attendance at religious services; religiosity; religious denomination; language usually spoken at home; region of residence; race; ethnicity; rural or urban residence; primary electoral district; country of birth; year arrived in current country.
Survey variables: perception of public expenditure on health, education, unemployment benefits, defense, old-age pensions, business and industry, police and law enforcement, welfare benefits; perception of improving individual standard of living, state of economy, government's action on income inequality; respondent cast a ballot at the current and the previous election; vote choice (presidential, lower house and upper house elections) at the current and the previous election; respondent cast candidate preference vote at the current and the previous election; difference who is in power and who people vote for; sympathy scale for selected parties and political leaders; assessment of parties on the left-right-scale and/or an alternative scale; self-assessment on a left-right-scale and an optional scale; satisfaction with democracy; party identification; intensity of party identification, institutional and personal contact in the electoral campaigning, in person, by mail, phone, text message, email or social networks, institutional contact by whom; political information questions; expected development of household income in the next twelve month; ownership of residence, business or property or farm or livestock, stocks or bonds, savings; likelihood to find another job within the next twelve month; spouse likelihood to find another job within the next twelve month.
DISTRICT-LEVEL DATA: number of seats contested in electoral district; number of candidates; number of party lists; percent vote of different parties; official voter turnout in electoral district.
MACRO-LEVEL DATA: election outcomes by parties in current (lower house/upper house) legislative election; percent of seats in lower house received by parties in current lower house/upper house election; percent of seats in upper house received by parties in current lower house/upper house election; percent of votes received by presidential candidate of parties in current elections; electoral turnout; party of the president and the prime minister before and after the election; number of portfolios held by each party in cabinet, prior to and after the most recent election; size of the cabinet after the most recent election; number of parties participating in election; ideological families of parties; left-right position of parties assigned by experts and alternative dimensions; most salient factors in the election; fairness of the election; formal complaints against national level results; election irregularities reported; scheduled and held date of election; irregularities of election date; extent of election violence and post-election violence; geographic concentration of violence; post-election protest; electoral alliances permitted during the election campaign; existing electoral alliances; requirements for joint party lists; possibility of apparentement and types of apparentement agreements; multi-party endorsements on ballot; votes cast; voting procedure; voting rounds; party lists close, open, or flexible; transferable votes; cumulated votes if more than one can be cast; compulsory voting; party threshold; unit for the threshold; freedom house rating; democracy-autocracy polity IV rating; age of the current regime; regime: type of executive; number of months since last lower house and last presidential election; electoral formula for presidential elections; electoral formula in all electoral tiers (majoritarian, proportional or mixed); for lower and upper houses was coded: number of electoral segments; linked electoral segments; dependent formulae in mixed systems; subtypes of mixed electoral systems; district magnitude (number of members elected from each district); number of secondary and tertiary electoral districts; fused vote; size of the lower house; GDP growth (annual percent); GDP per capita; inflation, GDP Deflator (annual percent); Human development index; total population; total unemployment; TI corruption perception index; international migrant stock and net migration rate; general government final consumption expenditure; public spending on education; health expenditure; military expenditure; central government debt; Gini index; internet users per 100 inhabitants; mobile phone subscriptions per 100 inhabitants; fixed telephone lines per 100 inhabitants; daily newspapers; constitutional federal structure; number of legislative chambers; electoral results data available; effective number of electoral and parliamentary parties.
BACKGROUND: Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. METHODS: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. FINDINGS: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89-4·12) annually, although it grew slower in per capita terms (2·72% [2·61-2·84]) and increased by less than $1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55% [5·18-5·95]), mainly due to growth in government health spending, and in lower-middle-income countries (3·71% [3·10-4·34]), mainly from DAH. Health spending globally reached $8·0 trillion (7·8-8·1) in 2016 (comprising 8·6% [8·4-8·7] of the global economy and $10·3 trillion [10·1-10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$5252 (5184-5319) in high-income countries, $491 (461-524) in upper-middle-income countries, $81 (74-89) in lower-middle-income countries, and $40 (38-43) in low-income countries. In 2016, 0·4% (0·3-0·4) of health spending globally was in low-income countries, despite these countries comprising 10·0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ($9·5 billion, 24·3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ($644·7 million in 2018). Globally, health spending is projected to increase to $15·0 trillion (14·0-16·0) by 2050 (reaching 9·4% [7·6-11·3] of the global economy and $21·3 trillion [19·8-23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1·84% (1·68-2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0·6% (0·6-0·7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130·2 (122·9-136·9) in 2016 and is projected to remain at similar levels in 2050 (125·9 [113·7-138·1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. INTERPRETATION: Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation ; Sí
The module was administered as a post-election interview. The resulting data are provided along with voting, demographic, district and macro variables in a single dataset.
CSES Variable Table The list of variables is being provided on the CSES Website to help in understanding what content is available from CSES, and to compare the content available in each module.
Themes:
MICRO-LEVEL DATA:
Identification and study administration variables: weighting factors; election type; date of election 1st and 2nd round; study timing (post-election study, pre-election and post-election study, between rounds of majoritarian election); mode of interview; gender of interviewer; date questionnaire administered; primary electoral district of respondent; number of days the interview was conducted after the election; language of questionnaire.
Demography: year and month of birth; gender; education; marital status; union membership; union membership of others in household; business association membership, farmers´ association membership; professional association membership; current employment status; main occupation; socio economic status; employment type - public or private; industrial sector; current employment status, occupation, socio economic status, employment type - public or private, and industrial sector of spouse; household income; number of persons in household; number of children in household under the age of 18; number of children in household under the age of 6; attendance at religious services; religiosity; religious denomination; language usually spoken at home; region of residence; race; ethnicity; rural or urban residence; primary electoral district; country of birth; year arrived in current country.
Survey variables: perception of public expenditure on health, education, unemployment benefits, defense, old-age pensions, business and industry, police and law enforcement, welfare benefits; perception of improving individual standard of living, state of economy, government's action on income inequality; respondent cast a ballot at the current and the previous election; vote choice (presidential, lower house and upper house elections) at the current and the previous election; respondent cast candidate preference vote at the current and the previous election; difference who is in power and who people vote for; sympathy scale for selected parties and political leaders; assessment of parties on the left-right-scale and/or an alternative scale; self-assessment on a left-right-scale and an optional scale; satisfaction with democracy; party identification; intensity of party identification, institutional and personal contact in the electoral campaigning, in person, by mail, phone, text message, email or social networks, institutional contact by whom; political information questions; expected development of household income in the next twelve month; ownership of residence, business or property or farm or livestock, stocks or bonds, savings; likelihood to find another job within the next twelve month; spouse likelihood to find another job within the next twelve month.
DISTRICT-LEVEL DATA: number of seats contested in electoral district; number of candidates; number of party lists; percent vote of different parties; official voter turnout in electoral district.
MACRO-LEVEL DATA: election outcomes by parties in current (lower house/upper house) legislative election; percent of seats in lower house received by parties in current lower house/upper house election; percent of seats in upper house received by parties in current lower house/upper house election; percent of votes received by presidential candidate of parties in current elections; electoral turnout; party of the president and the prime minister before and after the election; number of portfolios held by each party in cabinet, prior to and after the most recent election; size of the cabinet after the most recent election; number of parties participating in election; ideological families of parties; left-right position of parties assigned by experts and alternative dimensions; most salient factors in the election; fairness of the election; formal complaints against national level results; election irregularities reported; scheduled and held date of election; irregularities of election date; extent of election violence and post-election violence; geographic concentration of violence; post-election protest; electoral alliances permitted during the election campaign; existing electoral alliances; requirements for joint party lists; possibility of apparentement and types of apparentement agreements; multi-party endorsements on ballot; votes cast; voting procedure; voting rounds; party lists close, open, or flexible; transferable votes; cumulated votes if more than one can be cast; compulsory voting; party threshold; unit for the threshold; freedom house rating; democracy-autocracy polity IV rating; age of the current regime; regime: type of executive; number of months since last lower house and last presidential election; electoral formula for presidential elections; electoral formula in all electoral tiers (majoritarian, proportional or mixed); for lower and upper houses was coded: number of electoral segments; linked electoral segments; dependent formulae in mixed systems; subtypes of mixed electoral systems; district magnitude (number of members elected from each district); number of secondary and tertiary electoral districts; fused vote; size of the lower house; GDP growth (annual percent); GDP per capita; inflation, GDP Deflator (annual percent); Human development index; total population; total unemployment; TI corruption perception index; international migrant stock and net migration rate; general government final consumption expenditure; public spending on education; health expenditure; military expenditure; central government debt; Gini index; internet users per 100 inhabitants; mobile phone subscriptions per 100 inhabitants; fixed telephone lines per 100 inhabitants; daily newspapers; constitutional federal structure; number of legislative chambers; electoral results data available; effective number of electoral and parliamentary parties.
Das Modul wurde als Nachwahl-Befragung durchgeführt. Die daraus resultierenden Daten werden mit Daten über das Abstimmungsverhalten, demographischen Daten, und Variablen auf Wahlkreis- und Länderebene in einem einzelnen Datensatz bereitgestellt.
CSES Variable List
Eine Liste aller Variablen wird auf der Webseite des CSES bereitgestellt. Sie verdeutlicht, welche Inhalte über das CSES verfügbar sind und erlaubt es die Inhalte über verschiedene Module des CSES zu vergleichen.
Themen:
INDIVIDUALDATEN:
Technische Variablen: Gewichtungsvariablen; Art der Wahl; Datum der Wahl 1. und 2. Wahlgang; Zeitpunkt der Studie (Nachwahlbefragung, Vorwahlbefragung und Nachwahlbefragung, Zwischen Wahlgängen in Mehrheitswahlsystemen); Erhebungsmodus; Geschlecht des Interviewers; Datum der Datenerhebung; Wahlkreis des Befragten; Anzahl der Tage zwischen Wahltag und Interview.
Demographie: Alter; Geschlecht; Bildung; Familienstand; Gewerkschaftsmitgliedschaft; Gewerkschaftsmitgliedschaft anderer Haushaltsmitglieder; Mitgliedschaft in einem Unternehmerverband; Mitgliedschaft in Bauernverband; Mitgliedschaft in Berufsverband; Erwerbsstatus; Beruf; sozioökonomischer Status; Beschäftigungsform (öffentlicher oder privater Sektor, industrieller Sektor); Erwerbsstatus des Partners; Beruf des Partners; sozioökonomischer Status des Partners; Beschäftigungsform (öffentlicher oder privater Sektor, industrieller Sektor) des Partners; Haushaltseinkommen; Anzahl Personen im Haushalt; Anzahl Kinder im Haushalt; Anzahl Kinder unter 18 im Haushalt; Kirchgangshäufigkeit; Religiosität; Konfessionsmitgliedschaft; Haushaltssprache; Rasse; ethnische Zugehörigkeit; Wohnort; ländliches oder städtisches Wohnumfeld.
Befragungsvariablen: Wichtigste Themen der Wahl; Beurteilung der Kandidatenkompetenz im Umgang mit wichtigsten Themen der Wahl; Relevanz von Wahlen für Politikgestaltung; Bedeutung der eigenen Stimme für Politikgestaltung; Beurteilung der Leistung der Regierung; Partei und Spitzenpolitiker, die am besten für die Meinung des Befragten stehen; Sympathie-Skalometer für ausgewählte Parteien und Spitzenpolitiker; Einstufung von Parteien und Spitzenpolitikern auf einem Links-Rechts -Kontinuum; Selbsteinstufung auf Links-Rechts-Skala; wahrgenommene Unterschiede zwischen den zur Wahl stehenden Optionen; Beteiligung an der Wahlkampagne; Demokratiezufriedenheit; Parteiidentifikation; Intensität der Parteiidentifikation; Teilnahme bei der aktuellen und der letzten Wahl; Wahlentscheidung ( Präsidentschafts-, Unterhaus und Oberhauswahlen ) in der aktuellen und der letzten Wahl; Befragter hat Stimme für bevorzugten Kandidaten abgegeben; politische Informiertheit.
WAHLKREISDATEN:
Anzahl der zu vergebenden Sitze im Wahlkreis; Anzahl der Kandidaten im Wahlkreis; Anzahl der Parteilisten; Prozentanteil der Parteien (Wahlergebnis); Wahlbeteiligung im Wahlkreis.
LÄNDERDATEN:
Wahlergebnisse der Parteien bei der aktuellen Parlamentswahl (Unterhaus / Oberhaus); Anteil der von den Parteien erhaltenen Sitze im Unterhaus; Anteil der von den Parteien erhaltenen Sitze im Oberhaus; Anteil der Stimmen der Präsidentschaftskandidaten der Parteien bei der aktuellen Wahl; Wahlbeteiligung; Parteizugehörigkeit des Präsidenten und des Ministerpräsidenten vor und nach der Wahl; Anzahl der von jeder Partei gehaltenen Kabinettsposten vor und nach der letzten Wahl; Größe des Kabinetts nach der letzten Wahl; Anzahl der an der Wahl teilnehmenden Parteien; ideologische Parteifamilien; durch Experten zugeordnete Links-Rechts-Position der Parteien und alternative Dimensionen des Parteienwettbewerbs; bedeutendste Faktoren bei der Wahl; Fairness der Wahl; formelle Beschwerden gegen die Ergebnisse auf nationaler Ebene; Unregelmäßigkeiten bei den Wahlen; geplanter und tatsächlicher Wahltermin; Unregelmäßigkeiten des Wahltermins; Umfang von Gewalt während und nach der Wahl; geographische Konzentration von Gewalt; Protest nach der Wahl; Möglichkeit zu Wahlbündnisse im Wahlkampf; existierende Wahlbündnisse; Voraussetzungen für gemeinsame Parteilisten; Möglichkeit von Koalitionen ; Art der Vereinbarungen über Wahlbündnisse; Mehrparteien-Vermerke auf Stimmzetteln; Anzahl abgegebener Stimmen; Abstimmungsverfahren; Anzahl der Wahlgänge; Parteilisten geschlossen, offen oder flexibel; Stimmen übertragbar; Stimmen kumulierbar; Wahlpflicht; Sperrklausel; Einheit der Sperrklausel; Freedom House Rating; Polity-IV Klassifikation (Demokratie-Autokratie); Alter des gegenwärtigen Regimes; Eigenschaften des Regimes: Art der Exekutive, Anzahl der Monate seit den letzten Unterhauswahl und Präsidentschaftswahl; Wahlsystem bei Präsidentschaftswahlen, Wahlsystem für alle Wahlebenen (Mehrheitswahlrecht, Verhältniswahlrecht oder Mischformen); für Unter-und Oberhäuser wurde codiert: Anzahl der Wahlsegmente, verknüpfte Wahlsegmente, Unterformen von Mischwahlsystemen, Größenordnung des Bezirks (Anzahl der aus jedem Bezirk gewählten Mitglieder), Anzahl der sekundären und tertiären Wahlkreise, Stimmabgabe für Parteienbündnisse; Größe des Unterhauses; Wachstum des Bruttoinlandsprodukt (BIP) in Prozent; BIP pro Kopf; Inflationsrate, BIP- Deflator; Human-Development-Index; Gesamtbevölkerung; Arbeitslosigkeit absolut; föderale Verfassungsstruktur; Anzahl der gesetzgebenden Kammern; Verfügbarkeit der Wahlergebnisse; effektive Anzahl der Wahl- und Parlamentsparteien.
Das Modul wurde als Nachwahl-Befragung durchgeführt. Die daraus resultierenden Daten werden mit Daten über das Abstimmungsverhalten, demographischen Daten, und Variablen auf Wahlkreis- und Länderebene in einem einzelnen Datensatz bereitgestellt. CSES Variable List Eine Liste aller Variablen wird auf der Webseite des CSES bereitgestellt. Sie verdeutlicht, welche Inhalte über das CSES verfügbar sind und erlaubt es die Inhalte über verschiedene Module des CSES zu vergleichen. Themen: INDIVIDUALDATEN: Technische Variablen: Gewichtungsvariablen; Art der Wahl; Datum der Wahl 1. und 2. Wahlgang; Zeitpunkt der Studie (Nachwahlbefragung, Vorwahlbefragung und Nachwahlbefragung, Zwischen Wahlgängen in Mehrheitswahlsystemen); Erhebungsmodus; Geschlecht des Interviewers; Datum der Datenerhebung; Wahlkreis des Befragten; Anzahl der Tage zwischen Wahltag und Interview. Demographie: Alter; Geschlecht; Bildung; Familienstand; Gewerkschaftsmitgliedschaft; Gewerkschaftsmitgliedschaft anderer Haushaltsmitglieder; Mitgliedschaft in einem Unternehmerverband; Mitgliedschaft in Bauernverband; Mitgliedschaft in Berufsverband; Erwerbsstatus; Beruf; sozioökonomischer Status; Beschäftigungsform (öffentlicher oder privater Sektor, industrieller Sektor); Erwerbsstatus des Partners; Beruf des Partners; sozioökonomischer Status des Partners; Beschäftigungsform (öffentlicher oder privater Sektor, industrieller Sektor) des Partners; Haushaltseinkommen; Anzahl Personen im Haushalt; Anzahl Kinder im Haushalt; Anzahl Kinder unter 18 im Haushalt; Kirchgangshäufigkeit; Religiosität; Konfessionsmitgliedschaft; Haushaltssprache; Rasse; ethnische Zugehörigkeit; Wohnort; ländliches oder städtisches Wohnumfeld. Befragungsvariablen: Wichtigste Themen der Wahl; Beurteilung der Kandidatenkompetenz im Umgang mit wichtigsten Themen der Wahl; Relevanz von Wahlen für Politikgestaltung; Bedeutung der eigenen Stimme für Politikgestaltung; Beurteilung der Leistung der Regierung; Partei und Spitzenpolitiker, die am besten für die Meinung des Befragten stehen; Sympathie-Skalometer für ausgewählte Parteien und Spitzenpolitiker; Einstufung von Parteien und Spitzenpolitikern auf einem Links-Rechts -Kontinuum; Selbsteinstufung auf Links-Rechts-Skala; wahrgenommene Unterschiede zwischen den zur Wahl stehenden Optionen; Beteiligung an der Wahlkampagne; Demokratiezufriedenheit; Parteiidentifikation; Intensität der Parteiidentifikation; Teilnahme bei der aktuellen und der letzten Wahl; Wahlentscheidung ( Präsidentschafts-, Unterhaus und Oberhauswahlen ) in der aktuellen und der letzten Wahl; Befragter hat Stimme für bevorzugten Kandidaten abgegeben; politische Informiertheit. WAHLKREISDATEN: Anzahl der zu vergebenden Sitze im Wahlkreis; Anzahl der Kandidaten im Wahlkreis; Anzahl der Parteilisten; Prozentanteil der Parteien (Wahlergebnis); Wahlbeteiligung im Wahlkreis. LÄNDERDATEN: Wahlergebnisse der Parteien bei der aktuellen Parlamentswahl (Unterhaus / Oberhaus); Anteil der von den Parteien erhaltenen Sitze im Unterhaus; Anteil der von den Parteien erhaltenen Sitze im Oberhaus; Anteil der Stimmen der Präsidentschaftskandidaten der Parteien bei der aktuellen Wahl; Wahlbeteiligung; Parteizugehörigkeit des Präsidenten und des Ministerpräsidenten vor und nach der Wahl; Anzahl der von jeder Partei gehaltenen Kabinettsposten vor und nach der letzten Wahl; Größe des Kabinetts nach der letzten Wahl; Anzahl der an der Wahl teilnehmenden Parteien; ideologische Parteifamilien; durch Experten zugeordnete Links-Rechts-Position der Parteien und alternative Dimensionen des Parteienwettbewerbs; bedeutendste Faktoren bei der Wahl; Fairness der Wahl; formelle Beschwerden gegen die Ergebnisse auf nationaler Ebene; Unregelmäßigkeiten bei den Wahlen; geplanter und tatsächlicher Wahltermin; Unregelmäßigkeiten des Wahltermins; Umfang von Gewalt während und nach der Wahl; geographische Konzentration von Gewalt; Protest nach der Wahl; Möglichkeit zu Wahlbündnisse im Wahlkampf; existierende Wahlbündnisse; Voraussetzungen für gemeinsame Parteilisten; Möglichkeit von Koalitionen ; Art der Vereinbarungen über Wahlbündnisse; Mehrparteien-Vermerke auf Stimmzetteln; Anzahl abgegebener Stimmen; Abstimmungsverfahren; Anzahl der Wahlgänge; Parteilisten geschlossen, offen oder flexibel; Stimmen übertragbar; Stimmen kumulierbar; Wahlpflicht; Sperrklausel; Einheit der Sperrklausel; Freedom House Rating; Polity-IV Klassifikation (Demokratie-Autokratie); Alter des gegenwärtigen Regimes; Eigenschaften des Regimes: Art der Exekutive, Anzahl der Monate seit den letzten Unterhauswahl und Präsidentschaftswahl; Wahlsystem bei Präsidentschaftswahlen, Wahlsystem für alle Wahlebenen (Mehrheitswahlrecht, Verhältniswahlrecht oder Mischformen); für Unter-und Oberhäuser wurde codiert: Anzahl der Wahlsegmente, verknüpfte Wahlsegmente, Unterformen von Mischwahlsystemen, Größenordnung des Bezirks (Anzahl der aus jedem Bezirk gewählten Mitglieder), Anzahl der sekundären und tertiären Wahlkreise, Stimmabgabe für Parteienbündnisse; Größe des Unterhauses; Wachstum des Bruttoinlandsprodukt (BIP) in Prozent; BIP pro Kopf; Inflationsrate, BIP- Deflator; Human-Development-Index; Gesamtbevölkerung; Arbeitslosigkeit absolut; föderale Verfassungsstruktur; Anzahl der gesetzgebenden Kammern; Verfügbarkeit der Wahlergebnisse; effektive Anzahl der Wahl- und Parlamentsparteien.
Das Modul wurde als Nachwahl-Befragung durchgeführt. Die daraus resultierenden Daten werden mit Daten über das Abstimmungsverhalten, demographischen Daten, und Variablen auf Wahlkreis- und Länderebene in einem einzelnen Datensatz bereitgestellt.
CSES Variable List
Eine Liste aller Variablen wird auf der Webseite des CSES bereitgestellt. Sie verdeutlicht, welche Inhalte über das CSES verfügbar sind und erlaubt es die Inhalte über verschiedene Module des CSES zu vergleichen.
Themen:
INDIVIDUALDATEN:
Technische Variablen: Gewichtungsvariablen; Art der Wahl; Datum der Wahl 1. und 2. Wahlgang; Zeitpunkt der Studie (Nachwahlbefragung, Vorwahlbefragung und Nachwahlbefragung, Zwischen Wahlgängen in Mehrheitswahlsystemen); Erhebungsmodus; Geschlecht des Interviewers; Datum der Datenerhebung; Wahlkreis des Befragten; Anzahl der Tage zwischen Wahltag und Interview.
Demographie: Alter; Geschlecht; Bildung; Familienstand; Gewerkschaftsmitgliedschaft; Gewerkschaftsmitgliedschaft anderer Haushaltsmitglieder; Mitgliedschaft in einem Unternehmerverband; Mitgliedschaft in Bauernverband; Mitgliedschaft in Berufsverband; Erwerbsstatus; Beruf; sozioökonomischer Status; Beschäftigungsform (öffentlicher oder privater Sektor, industrieller Sektor); Erwerbsstatus des Partners; Beruf des Partners; sozioökonomischer Status des Partners; Beschäftigungsform (öffentlicher oder privater Sektor, industrieller Sektor) des Partners; Haushaltseinkommen; Anzahl Personen im Haushalt; Anzahl Kinder im Haushalt; Anzahl Kinder unter 18 im Haushalt; Kirchgangshäufigkeit; Religiosität; Konfessionsmitgliedschaft; Haushaltssprache; Rasse; ethnische Zugehörigkeit; Wohnort; ländliches oder städtisches Wohnumfeld.
Befragungsvariablen: Wichtigste Themen der Wahl; Beurteilung der Kandidatenkompetenz im Umgang mit wichtigsten Themen der Wahl; Relevanz von Wahlen für Politikgestaltung; Bedeutung der eigenen Stimme für Politikgestaltung; Beurteilung der Leistung der Regierung; Partei und Spitzenpolitiker, die am besten für die Meinung des Befragten stehen; Sympathie-Skalometer für ausgewählte Parteien und Spitzenpolitiker; Einstufung von Parteien und Spitzenpolitikern auf einem Links-Rechts -Kontinuum; Selbsteinstufung auf Links-Rechts-Skala; wahrgenommene Unterschiede zwischen den zur Wahl stehenden Optionen; Beteiligung an der Wahlkampagne; Demokratiezufriedenheit; Parteiidentifikation; Intensität der Parteiidentifikation; Teilnahme bei der aktuellen und der letzten Wahl; Wahlentscheidung ( Präsidentschafts-, Unterhaus und Oberhauswahlen ) in der aktuellen und der letzten Wahl; Befragter hat Stimme für bevorzugten Kandidaten abgegeben; politische Informiertheit.
WAHLKREISDATEN:
Anzahl der zu vergebenden Sitze im Wahlkreis; Anzahl der Kandidaten im Wahlkreis; Anzahl der Parteilisten; Prozentanteil der Parteien (Wahlergebnis); Wahlbeteiligung im Wahlkreis.
LÄNDERDATEN:
Wahlergebnisse der Parteien bei der aktuellen Parlamentswahl (Unterhaus / Oberhaus); Anteil der von den Parteien erhaltenen Sitze im Unterhaus; Anteil der von den Parteien erhaltenen Sitze im Oberhaus; Anteil der Stimmen der Präsidentschaftskandidaten der Parteien bei der aktuellen Wahl; Wahlbeteiligung; Parteizugehörigkeit des Präsidenten und des Ministerpräsidenten vor und nach der Wahl; Anzahl der von jeder Partei gehaltenen Kabinettsposten vor und nach der letzten Wahl; Größe des Kabinetts nach der letzten Wahl; Anzahl der an der Wahl teilnehmenden Parteien; ideologische Parteifamilien; durch Experten zugeordnete Links-Rechts-Position der Parteien und alternative Dimensionen des Parteienwettbewerbs; bedeutendste Faktoren bei der Wahl; Fairness der Wahl; formelle Beschwerden gegen die Ergebnisse auf nationaler Ebene; Unregelmäßigkeiten bei den Wahlen; geplanter und tatsächlicher Wahltermin; Unregelmäßigkeiten des Wahltermins; Umfang von Gewalt während und nach der Wahl; geographische Konzentration von Gewalt; Protest nach der Wahl; Möglichkeit zu Wahlbündnisse im Wahlkampf; existierende Wahlbündnisse; Voraussetzungen für gemeinsame Parteilisten; Möglichkeit von Koalitionen ; Art der Vereinbarungen über Wahlbündnisse; Mehrparteien-Vermerke auf Stimmzetteln; Anzahl abgegebener Stimmen; Abstimmungsverfahren; Anzahl der Wahlgänge; Parteilisten geschlossen, offen oder flexibel; Stimmen übertragbar; Stimmen kumulierbar; Wahlpflicht; Sperrklausel; Einheit der Sperrklausel; Freedom House Rating; Polity-IV Klassifikation (Demokratie-Autokratie); Alter des gegenwärtigen Regimes; Eigenschaften des Regimes: Art der Exekutive, Anzahl der Monate seit den letzten Unterhauswahl und Präsidentschaftswahl; Wahlsystem bei Präsidentschaftswahlen, Wahlsystem für alle Wahlebenen (Mehrheitswahlrecht, Verhältniswahlrecht oder Mischformen); für Unter-und Oberhäuser wurde codiert: Anzahl der Wahlsegmente, verknüpfte Wahlsegmente, Unterformen von Mischwahlsystemen, Größenordnung des Bezirks (Anzahl der aus jedem Bezirk gewählten Mitglieder), Anzahl der sekundären und tertiären Wahlkreise, Stimmabgabe für Parteienbündnisse; Größe des Unterhauses; Wachstum des Bruttoinlandsprodukt (BIP) in Prozent; BIP pro Kopf; Inflationsrate, BIP- Deflator; Human-Development-Index; Gesamtbevölkerung; Arbeitslosigkeit absolut; föderale Verfassungsstruktur; Anzahl der gesetzgebenden Kammern; Verfügbarkeit der Wahlergebnisse; effektive Anzahl der Wahl- und Parlamentsparteien.
The International Conferences on Economics and Social Sciences (ICESS)organized by Bucharest University of Economic Studies provides an opportunity for all those interested in Economics and Social Sciences to discuss and exchange research ideas. The papers presented at the Conference are available online in the Conference Proceedings series (ISSN 2704-6524): Volume 2019 Collaborative Research for Excellence in Economics and Social Sciences, ISBN 9788366675322 Volume 2020 Innovative Models to Revive the Global Economy, ISBN 9788395815072 This conference provides an opportunity for all those interested in Economics and Social Sciences to discuss and exchange research ideas. We welcome both empirical and theoretical work that is broadly consistent with the conference' general theme. Especially, researchers, PhD students and practitioners are invited to submit papers on the topics related to new models in entrepreneurship and innovation, sustainability and education, data science and digitalization, marketing and finance, Fintech & Insurtech etc. that will develop innovative instruments for countries, businesses and education. The innovative models for sustainable development aim to ensure simultaneous economic development, social development, and environmental protection, to achieve a higher quality of life for all people and protect all living beings and the planet. The main topics of the conference are focused on but not limited to the following sections: Fintech & Insurtech - towards a sustainable financial environment The role of innovation in public and private organizations Financial perspectives in turbulent times Global Challenges for Agri-Food Systems and Sustainable Development Economic Policies for Non-Cyclical Crises Education for Sustainable Development: impact of universities on society Marketing and Sustainability The role of accounting in Sustainable Development Global world after crisis: towards a new economic model Sustainability for future business Current challenges within demographic data: measurement, collection, retrieval, analysis and reporting We welcome you to join us for two intensive days of plenary speeches and specialized parallel sessions debates that will result in high quality practical insights and networking. Scientific CommitteeACELEANU Mirela, Bucharest University of Economic Studies, RomaniaALBU Lucian, Academia Romana, RomaniaANGHEL Ion, Bucharest University of Economic Studies, RomaniaARROYO GALLARDO Javier, Complutense University of Madrid, SpainAUSLOOS Marcel, Leicester University, United KingdomBEGALLI Diego, University of Verona, ItalyBELLINI Francesco, Sapienza University of Rome, ItalyBRATOSIN Ștefan, Universite Montpellier 3, FranceCABANIS Andre, Universite Toulouse 1 Capitole, FranceCASTERAN Herbert, EM Strasbourg University, FranceCENȚIU Silvian, Retina Communications, San Francisco, USACERQUETI Roy, Sapienza University of Rome, ItalyCHAVEZ Gilbert, Globis University Tokyo, JapanCOSTICÃ Ionela, Bucharest University of Economic Studies, RomaniaCOX Michael, London School of Economics, England, UKD'ASCENZO Fabrizio, Sapienza University of Rome, ItalyDIMA Alina Mihaela, Bucharest University of Economic Studies, RomaniaDÂRDALÃ Marian, Bucharest University of Economic Studies, RomaniaDUMITRESCU Dan Gabriel, Bucharest University of Economic Studies, RomaniaDUMITRU Ovidiu, Bucharest University of Economic Studies, RomaniaFELEAGÃ Liliana, Bucharest University of Economic Studies, RomaniaFONSECA Luis Miguel, Polytechnic of Porto, PortugalGARCÍA-GOÑI Manuel, Universitad Complutense de Madrid, SpainGIUDICI Paolo, The University of Pavia, ItalyGRUBOR Aleksandar, University of Novi Sad, SerbiaHÄRDLE Wolfgang Karl, Humboldt University of Berlin, GermanyHURDUZEU Gheorghe, Bucharest University of Economic Studies, RomaniaISTUDOR Nicolae, Bucharest University of Economic Studies, RomaniaKOKUSHO Kyoko, IBM Tokyo, JapanLOMBARDI Mariarosaria, University of Foggia, ItalyMEHMANPAZIR Babak, EM Strasbourg University, FranceMIRON Dumitru, Bucharest University of Economic Studies, RomaniaNABIRUKHINA Anna Vadimovna, Saint Petersburg State University, RussiaNICA Elvira, Bucharest University of Economic Studies, RomaniaNIJKAMP Peter, Jeronimus Academy of Data Science Den Bosch, NetherlandsNOVO CORTI Maria Isabel, Universidade da Coruña, SpainORDÓÑEZ MONFORT Javier, Jaume I University, SpainPANETTA Roberto, Bocconi University, ItalyPARASCHIV Dorel Mihai, Bucharest University of Economic Studies, RomaniaPICATOSTE Xose, Universidad Autonoma de Madrid, SpainPIROȘCÃ Grigore, Bucharest University of Economic Studies, RomaniaPOINT Sébastien, EM Strasbourg University, FrancePOPA Ion, Bucharest University of Economic Studies, RomaniaPROFIROIU Marius Constantin, Bucharest University of Economic Studies, RomaniaRICHMOND Peter, Trinity College Dublin, IrelandSÂRBU Roxana, Bucharest University of Economic Studies, RomaniaSINGER Slavica, J.J. Strossmayer University of Osijek, CroatiaSMEUREANU Ion, Bucharest University of Economic Studies, RomaniaSTAMULE Tãnase, Bucharest University of Economic Studies, RomaniaSTATE Radu, University of Luxembourg, LuxembourgSTOIAN Mirela, Bucharest University of Economic Studies, RomaniaSTRAT Vasile Alecsandru, Bucharest University of Economic Studies, RomaniaSTREET Donna, University of Dayton, USATEIXEIRA DOMINGUES José Pedro, University of Minho, PortugalȚIGU Gabriela, Bucharest University of Economic Studies, RomaniaVALDEBENITO Carlos Ramirez, University of Chile, Santiago de Chile, ChileVEGHEȘ Cãlin Petricã, Bucharest University of Economic Studies, RomaniaVERHOEF Peter, University of Groningen, NetherlandsVOLKMANN Christine Katharina, Schumpeter School of Business and Economics, Bergische Universität Wuppertal, GermanyWALTER FARKAS Erich, University of Zurich, SwitzerlandWIERENGA Berend, Rotterdam School of Management, NetherlandsWOODS Michael, University of Aberystwyth, Wales, UKZIMMERMANN Klaus F., Bonn University (em.) end Global Labor Organization, Germany Open Access Statement These conference proceedings are Open Access proceedings that allow a free unlimited access to all its contents without any restrictions upon publication to all users. Open Access License These conference proceedings provide immediate open access to its content under the Creative Commons BY-NC-ND 4.0. Authors who publish with these proceedings retain all copyrights and agree to the terms of the above-mentioned CC BY-NC-ND 4.0 license. ABSTRACTING & INDEXING Innovative Models to Revive the Global Economy is covered by the following services: Directory of Open Access Books (DOAB) EBSCO Discovery Service Google Scholar Naviga (Softweco) Primo Central (ExLibris) ReadCube Summon (ProQuest) TDOne (TDNet) WorldCat (OCLC)
Das CSES Module 5 (2016-2021) legt den Schwerpunkt auf "the politics of populism", also auf Populismus. Es erforscht länderübergreifend den Zusammenhang zwischen dem Aufstieg von populistischen Parteien und der Verteilung von "populistischen" Einstellungen innerhalb der Bevölkerung. Hauptziel des Moduls ist es, die Auffassungen der BürgerInnen von politischen Eliten, gesellschaftlichen "Out-Groups" und nationaler Identität sowie die sich hieraus ergebenden Implikationen für repräsentative Demokratien zu analysieren. Die Daten erlauben es Forschenden somit, die Variation im Wettbewerb politischer Eliten und "populistischer" Einstellungen über Demokratien hinweg mit einzubeziehen, und zu untersuchen, wie solche Wahrnehmungen das Wahlverhalten von BürgerInnen beeinflussen.
Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding: Bill & Melinda Gates Foundation.
BACKGROUND: Traumatic brain injury (TBI) and spinal cord injury (SCI) are increasingly recognised as global health priorities in view of the preventability of most injuries and the complex and expensive medical care they necessitate. We aimed to measure the incidence, prevalence, and years of life lived with disability (YLDs) for TBI and SCI from all causes of injury in every country, to describe how these measures have changed between 1990 and 2016, and to estimate the proportion of TBI and SCI cases caused by different types of injury. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 to measure the global, regional, and national burden of TBI and SCI by age and sex. We measured the incidence and prevalence of all causes of injury requiring medical care in inpatient and outpatient records, literature studies, and survey data. By use of clinical record data, we estimated the proportion of each cause of injury that required medical care that would result in TBI or SCI being considered as the nature of injury. We used literature studies to establish standardised mortality ratios and applied differential equations to convert incidence to prevalence of long-term disability. Finally, we applied GBD disability weights to calculate YLDs. We used a Bayesian meta-regression tool for epidemiological modelling, used cause-specific mortality rates for non-fatal estimation, and adjusted our results for disability experienced with comorbid conditions. We also analysed results on the basis of the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, there were 27·08 million (95% uncertainty interval [UI] 24·30-30·30 million) new cases of TBI and 0·93 million (0·78-1·16 million) new cases of SCI, with age-standardised incidence rates of 369 (331-412) per 100 000 population for TBI and 13 (11-16) per 100 000 for SCI. In 2016, the number of prevalent cases of TBI was 55·50 million (53·40-57·62 million) and of SCI was 27·04 million (24·98-30·15 million). From 1990 to 2016, the age-standardised prevalence of TBI increased by 8·4% (95% UI 7·7 to 9·2), whereas that of SCI did not change significantly (-0·2% [-2·1 to 2·7]). Age-standardised incidence rates increased by 3·6% (1·8 to 5·5) for TBI, but did not change significantly for SCI (-3·6% [-7·4 to 4·0]). TBI caused 8·1 million (95% UI 6·0-10·4 million) YLDs and SCI caused 9·5 million (6·7-12·4 million) YLDs in 2016, corresponding to age-standardised rates of 111 (82-141) per 100 000 for TBI and 130 (90-170) per 100 000 for SCI. Falls and road injuries were the leading causes of new cases of TBI and SCI in most regions. INTERPRETATION: TBI and SCI constitute a considerable portion of the global injury burden and are caused primarily by falls and road injuries. The increase in incidence of TBI over time might continue in view of increases in population density, population ageing, and increasing use of motor vehicles, motorcycles, and bicycles. The number of individuals living with SCI is expected to increase in view of population growth, which is concerning because of the specialised care that people with SCI can require. Our study was limited by data sparsity in some regions, and it will be important to invest greater resources in collection of data for TBI and SCI to improve the accuracy of future assessments. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation ; We acknowledge the funding and support of the Bill & Melinda Gates Foundation. AK was supported by the Miguel Servet contract, which was financed by the CP13/00150 and PI15/00862 projects integrated into the National Research, Development, and Implementation,and funded by the Instituto de Salud Carlos III General Branch Evaluation and Promotion of Health Research and the European Regional Development Fund (ERDF-FEDER). AMS is supported by the Egyptian Fulbright Mission Program. AF acknowledges the Federal University of Sergipe (Sergipe, Brazil). AA received financial assistance from the Indian Department of Science and Technology (New Delhi, India) through the INSPIRE faculty programme. AS is supported by Health Data Research UK. DJS is supported by the South African Medical Research Council. AB is supported by the Public Health Agency of Canada. SMSI received a senior research fellowship from the Institute for Physical Activity and Nutrition, Deakin University (Waurn Ponds, VIC, Australia), and a career transition grant from the High Blood Pressure Research Council of Australia. FP and CF acknowledge support from the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e a Tecnologia, and Ministério da Educação e Ciência) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020 UID/QUI/50006/2013. TB acknowledges financial support from the Institute of Medical Research and Medicinal Plant Studies, Yaoundé, Cameroon. AM of Imperial College London is grateful for support from the Northwest London National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research andCare and the Imperial NIHR Biomedical Research Centre. KD is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (grant number 201900). PSA is supported by an Australian National Health and Medical Research Council Early Career Fellowship. RT-S was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. The Serbian part of this contribution (by MJ) has been co-financed with grant OI175014 from the Serbian Ministry of Education, Science and Technological Development; publication of results was not contingent upon the Ministry's approval. MMMSM acknowledges support from the Serbian Ministry of Education, Science and Technological Development (contract 175087). MM's research was supported by the NIHR Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust (London, UK) and King's College London. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the UK Department of Health. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt professor award, which was funded by the German Federal Ministry of Education and Research ; Sí
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