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European Union Survey of Income and Living Conditions (EU-SILC), 2022
No full textThe primary focus of the Survey on Income and Living Conditions (SILC) is the collection of information on the income and living conditions of different types of households in Ireland, in order to derive indicators on poverty, deprivation and social exclusion. It is a voluntary survey of private households. The SILC Anonymised Microdata File (AMF) contains both personal and household level data. Household data is at present duplicated for each member of the household. If performing household level analysis, please be aware of this and subset the data to include a single entry per household (interview_hh = 1). In 2021 the European legislative basis (Regulation No 1177/2003) for the production of statistics on income and living conditions has been repealed by Regulation 2019/1700. This new framework regulation establishes a common framework for European statistics relating to persons and households, based on data at individual level collected by samples. In order to meet the requirements of the new regulation, the Central Statistics Office (CSO) introduced changes to many SILC business processes. These changes have resulted in a break in the SILC time series for 2020.Data from 2020 onwards is not directly comparable with data from 2004-2019. To make the difference clear, national use variables from 2020 onwards have been re-named. Census Revision to SILC 2020-SILC 2022 The annual Survey of Income and Living Condition (SILC) results are weighted using population estimates which are generated on an ongoing basis. Census of Population 2022 results have been used to revise population estimates for 2020 to 2022, and consequently results for SILC survey years 2020, 2021 and 2022 are revised. Please note: SILC AMF data is cross-sectional microdata in which household and/or individuals cannot be tracked over time. The household id variables in each cross sectional file are randomly generated and cannot be linked between yearly datasets.<br
Growing Up in Ireland (GUI) Cohort ’08 (Infant Cohort) Wave 3 - 5 years, 2013
No full textGrowing Up in Ireland - the National Longitudinal Study of Children, is the first survey of its kind ever undertaken in Ireland and, as such, aims to explore the many and varied factors that contribute to or undermine the wellbeing of children currently living there. A two age cohort longitudinal design was adopted with one cohort of 11,134 infants (aged nine months) and the other of 8,568 nine-year olds, with a view to improving and understanding of children’s development across a range of domains. Since the survey is longitudinal in nature respondents in both cohorts are interviewed on a number of occasions over the folowing few years. The 11,134 children representing the infant cohort were born between 1st December 2007 and the 30th June 2008 and data collection for the first wave at age 9 months took place between September 2008 and April 2009. The third wave of data collection took place between March and September 2013, when the cohort were 5 years of age, resulting in a completed data file of 9,001 cases
Thesaurus for the Social Sciences (SKOS version)
No full textThe Thesaurus for the Social Sciences (TheSoz) contains about 12,000 entries, of which more than 8,000 are descriptors (authorised keywords) and about 6,000 non-descriptors. Topics from all disciplines of the social sciences are covered. This SKOS version of the thesaurus contains descriptors and non-descriptors in four languages (German, English, French, and Russian) as well as links to the TheSoz Classification, the STW Thesaurus for Economics, the AGROVOC Multilingual Thesaurus, and to DBpedia. The TheSoz Classification (TheSoz-CL) is a topic hierarchy complementing the Thesaurus for the Social Sciences (TheSoz). Within this SKOS version of the classification, individual classification items contain links to entries from the TheSoz. The zip archive contains the following files: - thesoz.ttl: the SKOS version of the TheSoz in Turtle format - thesoz_classification.ttl: the SKOS version of the TheSoz Classification in Turtle format - readme.txt: readme fileThe Thesaurus for the Social Sciences (TheSoz) contains about 12,000 entries, of which more than 8,000 are descriptors (authorised keywords) and about 6,000 non-descriptors. Topics from all disciplines of the social sciences are covered. This SKOS version of the thesaurus contains descriptors and non-descriptors in four languages (German, English, French, and Russian) as well as links to the TheSoz Classification, the STW Thesaurus for Economics, the AGROVOC Multilingual Thesaurus, and to DBpedia. The TheSoz Classification (TheSoz-CL) is a topic hierarchy complementing the Thesaurus for the Social Sciences (TheSoz). Within this SKOS version of the classification, individual classification items contain links to entries from the TheSoz. The zip archive contains the following files: - thesoz.ttl: the SKOS version of the TheSoz in Turtle format - thesoz_classification.ttl: the SKOS version of the TheSoz Classification in Turtle format - readme.txt: readme fil
The EurLocalTurnout Dataset
No full textAbstract: The EurLocalTurnout Dataset contains electoral data at the municipal level for both national and local elections in 18 European countries - Austria, Czech Republic, Denmark, Finland, France, Germany, Iceland, Italy, Latvia, Liechtenstein, Luxembourg, Netherlands, Norway, Poland, Romania, Slovakia, Spain, Sweden. In addition, a number of relevant institutional, economic, cultural, and demographic measures are included. All variables were recorded in the period 2013-2020.Abstract: The EurLocalTurnout Dataset contains electoral data at the municipal level for both national and local elections in 18 European countries - Austria, Czech Republic, Denmark, Finland, France, Germany, Iceland, Italy, Latvia, Liechtenstein, Luxembourg, Netherlands, Norway, Poland, Romania, Slovakia, Spain, Sweden. In addition, a number of relevant institutional, economic, cultural, and demographic measures are included. All variables were recorded in the period 2013-2020
Replication files: Global Motivation to Learn and Adult Learning: A Nomological Network Analysis and a Four-Year Longitudinal Study
No full textThis contribution contains data and script files to replicate results from the following article: Gorges, J. (2025). Global Motivation to Learn and Adult Learning: A Nomological Network Analysis and a Four-Year Longitudinal Study. Learning an Individual Differences. The article reports on a study investigating motivation to learn (MtL), conceptualized at a global level of abstraction (i.e., independent of specific educational settings such as high school or university, and independent of learning content such as school subjects) in adult learning. In Study 1 (N = 747, 65.1% female; age: M[SD] = 43.21[12.09] years), the analysis of the nomological network of global MtL revealed strong correlations with mastery goal orientation, an adapted measure of intrinsic task value, need for cognition, and self-concept of ability, as well as moderate correlations with openness and conscientiousness. Cross-sectional associations with (past and planned) participation in education were small to moderate. Based on the representative German PIAAC longitudinal study covering four years (Nt1 = 4191, Nt2 = 2502, Nt3 = 2370), Study 2 tested the role of MtL as a predictor of participation in non-formal and informal adult education and training was tested using structural equation modeling, controlling for level of education, employment, literacy, age, and sex. Results support the hypothesis that global MtL predicts participation in adult education and training while controlling for typical sociodemographic determinants (e.g., level of education, employment). Openness was tested as a competitor of global MtL but failed to show a significant effect on participation in education. The results are discussed with respect to theoretical implications for the development of motivation theory and practical implications for the promotion of lifelong learning. Data to replicate results from Study 1 are included, PIAAC data to replicate results from Study 2 must be obtained from GESIS (see data file section for details).This contribution contains data and script files to replicate results from the following article: Gorges, J. (2025). Global Motivation to Learn and Adult Learning: A Nomological Network Analysis and a Four-Year Longitudinal Study. Learning an Individual Differences. The article reports on a study investigating motivation to learn (MtL), conceptualized at a global level of abstraction (i.e., independent of specific educational settings such as high school or university, and independent of learning content such as school subjects) in adult learning. In Study 1 (N = 747, 65.1% female; age: M[SD] = 43.21[12.09] years), the analysis of the nomological network of global MtL revealed strong correlations with mastery goal orientation, an adapted measure of intrinsic task value, need for cognition, and self-concept of ability, as well as moderate correlations with openness and conscientiousness. Cross-sectional associations with (past and planned) participation in education were small to moderate. Based on the representative German PIAAC longitudinal study covering four years (Nt1 = 4191, Nt2 = 2502, Nt3 = 2370), Study 2 tested the role of MtL as a predictor of participation in non-formal and informal adult education and training was tested using structural equation modeling, controlling for level of education, employment, literacy, age, and sex. Results support the hypothesis that global MtL predicts participation in adult education and training while controlling for typical sociodemographic determinants (e.g., level of education, employment). Openness was tested as a competitor of global MtL but failed to show a significant effect on participation in education. The results are discussed with respect to theoretical implications for the development of motivation theory and practical implications for the promotion of lifelong learning. Data to replicate results from Study 1 are included, PIAAC data to replicate results from Study 2 must be obtained from GESIS (see data file section for details)
JOLanDA Jugendbefragung 2022
No full textDie Daten wurden im Rahmen des durch das BMBF geförderten transdisziplinären Forschungsprojektes JOLanDA erhoben. Ziel der Studie war die Modellierung des Zusammenhanges der beiden Lebenslaufentscheidungen Berufswahl und Wohnortentscheidung im Rahmen einer Strukturgleichungsanalyse. Die standardisierte Schulklassenbefragung in den Jahrgangsstufen acht, neun und zehn umfasste die Themenkomplexe allgemeine Fragen zu Wohnort und Region, Einstellungen zur Region, Regionale Bindung und Raumpräferenz, Wohnortentscheidung, Berufswahlkompetenz, Berufswahlentscheidung, Soziale Unterstützung, Auswirkungen der Corona-Pandemie sowie einen soziodemographischen Block. Ein besonderer Fokus der Studie lag auf dem Vergleich unterschiedlicher Raumtypen. Hierzu wurden Jugendliche kontrastierend in einer ländlich-peripheren Flächenregion in Niedersachsen sowie in der Landeshauptstadt befragt. Die Stichprobe umfasst insgesamt 803 Datensätze.Die Daten wurden im Rahmen des durch das BMBF geförderten transdisziplinären Forschungsprojektes JOLanDA erhoben. Ziel der Studie war die Modellierung des Zusammenhanges der beiden Lebenslaufentscheidungen Berufswahl und Wohnortentscheidung im Rahmen einer Strukturgleichungsanalyse. Die standardisierte Schulklassenbefragung in den Jahrgangsstufen acht, neun und zehn umfasste die Themenkomplexe allgemeine Fragen zu Wohnort und Region, Einstellungen zur Region, Regionale Bindung und Raumpräferenz, Wohnortentscheidung, Berufswahlkompetenz, Berufswahlentscheidung, Soziale Unterstützung, Auswirkungen der Corona-Pandemie sowie einen soziodemographischen Block. Ein besonderer Fokus der Studie lag auf dem Vergleich unterschiedlicher Raumtypen. Hierzu wurden Jugendliche kontrastierend in einer ländlich-peripheren Flächenregion in Niedersachsen sowie in der Landeshauptstadt befragt. Die Stichprobe umfasst insgesamt 803 Datensätze
Verzeichnis der Industriedenkmale in den Regionen Deutschlands
No full text--- see English below --- Der Datensatz enthält die Anzahl der Industriedenkmale deutscher Regionen (NUTS-3, Raumordnungsregionen, Arbeitsmarktregionen) gesamt sowie unterteilt nach den drei Bereichen 'Produktion', 'Versorgung' und 'Verkehr'. Darüber hinaus werden diese absoluten Werte in Relation zur Fläche der Region (je 10 km²) und der Bevölkerungsdichte (pro 1.000 Einwohner) gesetzt. Die Rohdaten wurden von den entsprechenden Denkmalbehörden Deutschlands gesammelt und ein Wörterbuch mit Stichworten zur Identifizierung von Industriedenkmalen erstellt. --- The dataset contains the number of industrial monuments in German regions (NUTS-3, spatial planning regions, labor market regions) as a whole and broken down into the three areas of 'production', 'supply' and ' traffic'. In addition, these absolute values are set in relation to the area of the region (per 10 km²) and the population density (per 1,000 inhabitants). The raw data was collected from the relevant monument authorities in Germany and a dictionary with keywords for identifying industrial monuments was compiled.--- see English below --- Der Datensatz enthält die Anzahl der Industriedenkmale deutscher Regionen (NUTS-3, Raumordnungsregionen, Arbeitsmarktregionen) gesamt sowie unterteilt nach den drei Bereichen 'Produktion', 'Versorgung' und 'Verkehr'. Darüber hinaus werden diese absoluten Werte in Relation zur Fläche der Region (je 10 km²) und der Bevölkerungsdichte (pro 1.000 Einwohner) gesetzt. Die Rohdaten wurden von den entsprechenden Denkmalbehörden Deutschlands gesammelt und ein Wörterbuch mit Stichworten zur Identifizierung von Industriedenkmalen erstellt. --- The dataset contains the number of industrial monuments in German regions (NUTS-3, spatial planning regions, labor market regions) as a whole and broken down into the three areas of 'production', 'supply' and ' traffic'. In addition, these absolute values are set in relation to the area of the region (per 10 km²) and the population density (per 1,000 inhabitants). The raw data was collected from the relevant monument authorities in Germany and a dictionary with keywords for identifying industrial monuments was compiled
Vietnam Special Economic Zone Satellite Imagery Dataset
No full textThe dataset contains detailed geographic information on more than 600 Special Economic Zones (SEZs) in Vietnam. Specifically, it captures the exact location (latitude and longitude) as well as changes in the built-up area of each of SEZ over time. The change in built-up area over time is calculated from manually drawn polygons around the built-up area of each SEZ on historical satellite imagery from Google Earth Pro. We provide access to these polygons for each SEZ in the KLM file ‘Vietnam SEZ Polygons.klm’ and the built-up area over time for each SEZ in the STATA file ‘Vietnam SEZ Built-up Areas.dta’. We also provide access to additional metadata on each SEZ – including zone type, focus sector, and year of approval/establishment – in the Excel file ‘Vietnam SEZ Metadata.xlsx’.The dataset contains detailed geographic information on more than 600 Special Economic Zones (SEZs) in Vietnam. Specifically, it captures the exact location (latitude and longitude) as well as changes in the built-up area of each of SEZ over time. The change in built-up area over time is calculated from manually drawn polygons around the built-up area of each SEZ on historical satellite imagery from Google Earth Pro. We provide access to these polygons for each SEZ in the KLM file ‘Vietnam SEZ Polygons.klm’ and the built-up area over time for each SEZ in the STATA file ‘Vietnam SEZ Built-up Areas.dta’. We also provide access to additional metadata on each SEZ – including zone type, focus sector, and year of approval/establishment – in the Excel file ‘Vietnam SEZ Metadata.xlsx’
Modern State (November 2024)
No full textThe study on the modern state was conducted by dimap on behalf of the Press and Information Office of the Federal Government. In the survey period 04.11.2024 - 16.11.2024, the population aged 16 and over in Germany was surveyed in telephone interviews (CATI) on the following topics: citizens´ expectations of a modern state, democracy and understanding of the state, responsibility of the state, economy and population, evaluation of administration, offices and authorities and own experiences, trust in state institutions and actors. Respondents were selected using a multi-stage random sample based on the RDD method, including landline and mobile phone numbers (dual-frame sample). The findings are supplemented by the results of 24 qualitative individual interviews that GIM conducted with people in Essen, Berlin, Munich and Dresden from November 11 to 19, 2024. The report on the results of this qualitative study is available to the archive, but not the corresponding data.1. Democracy and understanding of the state: satisfaction with democracy; democracy as the best form of government for Germany; preferred level of decision-making for important political decisions: by citizens, e.g. in referendums or by elected politicians in referendums or by elected politicians; agreement with various statements on the subject of the state and citizens (the state interferes too much in our lives, the opinion of the population is not taken into account enough in important political decisions, citizens are well informed in the run-up to important political decisions, people should not rely so much on the state but should tackle their problems themselves more); areas with too much state regulation (open-ended response); areas where there should be more state regulation (open-ended response). 2. Responsibility of the state, economy and population: assessment of the commitment of the German state and federal government to tackle the problems in the following areas: Climate change and its consequences, reception and integration of refugees, Germany´s economic development, right-wing extremism, inflation and price increases, state of social cohesion); assessment of citizens´ commitment to tackling the problems in the aforementioned areas; agreement with various statements (There are too many federal ministries, so some should be abolished, the federal government is dealing with too many issues at the same time, the federal government is dealing with the most important issues at the moment, I have a good overview of what measures the federal government has adopted in the last year); better results by the state vs. private companies in the provision of services in various areas (health care, nursing care, local public transport, road construction, waste disposal and housing); state responsibility or personal responsibility in various areas (protection against crime, protection against the spread of epidemics and epidemics, environmental and climate protection, protection against impoverishment, protection in the event of illness, financial security in old age); personal benefits from the welfare state. 3. Administration, offices and authorities: evaluation of the services provided by public offices and authorities in recent years (rather improved, rather worsened, has not changed that much); characterization of the actions of public offices and authorities using pairs of opposites (bureaucratic - unbureaucratic, supportive - patronizing, fair - unfair, slow - fast, efficient -inefficient, comprehensible - incomprehensible, corruptible - incorruptible); Satisfaction with the last contact with a public authority or administration; assessment of the effort involved in dealing with public authorities; change in the effort involved in dealing with public authorities in recent years; public authorities should exchange more data in order to reduce the effort vs. avoid more exchange for data protection reasons; importance of being able to deal with public authority matters online or on the Internet. 4. Trust in state institutions and actors: trust in the federal government, in offices and authorities, in the state government and in the mayor of the municipality; in Germany, the right people are in the leading positions. Demography: sex; age; federal state; East or West Berlin; size of location; highest level of education; party preference. Additionally coded: consecutive respondent number; weight.Die Studie über den modernen Staat wurde von dimap im Auftrag des Presse- und Informationsamts der Bundesregierung durchgeführt. Im Erhebungszeitraum 04.11.2024 – 16.11.2024 wurde die Bevölkerung ab 16 Jahren in Deutschland in telefonischen Interviews (CATI) zu folgenden Themen befragt: Erwartungen der Bürgerinnen und Bürger an einen modernen Staat, Demokratie und Staatsverständnis, Verantwortung von Staat, Wirtschaft und Bevölkerung, Bewertung von Verwaltung, Ämtern und Behörden und eigene Erfahrungen, Vertrauen in staatliche Institutionen und Akteure. Die Auswahl der Befragten erfolgte durch eine mehrstufige Zufallsstichprobe nach dem RDD-Verfahren unter Einschluss von Festnetz- und Mobilfunknummern (Dual-Frame Stichprobe). Ergänzt werden die Befunde durch die Ergebnisse aus 24 qualitativen Einzelinterviews, die GIM vom 11. bis 19. November 2024 mit Menschen in Essen, Berlin, München und Dresden durchgeführt hat. Der Ergebnisbericht zu dieser qualitativen Studie liegt dem Archiv vor, nicht jedoch die entsprechenden Daten.1. Demokratie und Staatsverständnis: Demokratiezufriedenheit; Demokratie als beste Staatsform für Deutschland; präferierte Entscheidungsebene für wichtige politische Entscheidungen: durch Bürgerinnen und Bürger z.B. in Volksabstimmungen oder durch gewählte Politikerinnen und Politiker; Zustimmung zu verschiedenen Aussagen zum Thema Staat und Bürger (Der Staat mischt sich zu sehr in unser Leben ein, die Meinung der Bevölkerung wird bei wichtigen politischen Entscheidungen zu wenig berücksichtigt, die Bürgerinnen und Bürger werden im Vorfeld wichtiger politischer Entscheidungen gut informiert, die Menschen sollten sich nicht so sehr auf den Staat verlasen, sondern ihre Probleme stärker selbst in Angriff nehmen); Bereiche mit zu viel staatlichen Regelungen (offene Nennung); Bereiche wo es mehr staatliche Regelungen geben sollte (offene Nennung). 2. Verantwortung von Staat, Wirtschaft und Bevölkerung: Bewertung des Engagements des deutschen Staates und der Bundesregierung zur Bewältigung der Probleme in folgenden Bereichen: Klimawandel und seine Folgen, Aufnahme und Integration von Flüchtlingen, wirtschaftliche Entwicklung Deutschlands, Rechtsextremismus, Inflation und Preissteigerungen, Zustand des gesellschaftlichen Zusammenhalts); Bewertung des Engagements der Bürgerinnen und Bürger zur Bewältigung der Probleme in den vorgenannten Bereichen; Zustimmung zu verschiedenen Aussagen (Es gibt zu viele Bundesministerien, daher sollten einige abgeschafft werden, die Bundesregierung beschäftigt sich mit zu vielen Themen gleichzeitig, die Bundesregierung kümmert sich um die derzeit wichtigsten Themen, ich habe einen guten Überblick darüber, welche Maßnahmen die Bundesregierung im letzten Jahr verabschiedet hat); bessere Ergebnisse durch den Staat vs. private Unternehmen bei der Erbringung von Leistungen in verschiedenen Bereichen (Krankenversorgung, Pflege, öffentlicher Personennahverkehr, Straßenbau, Müllentsorgung und Wohnungsbau); staatliche Verantwortung oder Eigenverantwortung in verschiedenen Bereichen (Schutz vor Kriminalität, Schutz vor der Ausbreitung von Seuchen und Epidemien, Umwelt- und Klimaschutz, Schutz vor Verarmung, Absicherung im Krankheitsfall, finanzielle Absicherung im Alter); persönliche Vorteile durch den Sozialstaat. 3. Verwaltung, Ämter und Behörden: Bewertung der Services von Ämtern und Behörden in den letzten Jahren (eher verbessert, eher verschlechtert, hat sich nicht so viel verändert); Charakterisierung des Handelns von Ämtern und Behörden anhand von Gegensatzpaaren (bürokratisch – unbürokratisch, unterstützend – bevormundend, gerecht – ungerecht, langsam – schnell, effizient -ineffizient, nachvollziehbar – unverständlich, bestechlich – unbestechlich); Zufriedenheit mit dem letzten Kontakt mit einer Behörde oder Verwaltung; Bewertung des Aufwands für Behördenangelegenheiten; Veränderung des Aufwands für Behördenangelegenheiten in den letzten Jahren; Behörden sollten verstärkt Daten austauschen, um den Aufwand zu reduzieren vs. aus Datenschutzgründen auf mehr Austausch verzichten; Wichtigkeit der Möglichkeit, Behördenangelegenheiten online oder im Internet zu erledigen. 4. Vertrauen in staatliche Institutionen und Akteure: Vertrauen in die Bundesregierung, in Ämter und Behörden, in die Landesregierung sowie in den Bürgermeister oder die Bürgermeisterin der Gemeinde; in Deutschland sind die richtigen Leute in den führenden Positionen. Demographie: Geschlecht; Alter; Bundesland; Berlin Ost oder West; Ortsgröße; höchster Bildungsabschluss; Parteipräferenz. Zusätzlich verkodet wurde: laufende Befragtennummer; Gewicht
Current Questions on the Federal Budget (July 2024)
No full textThe short survey on the federal budget was conducted by forsa on behalf of the Press and Information Office of the Federal Government. In the survey period from 18.07.2024 to 22.07.2024, the German-speaking population aged 14 and over in private households was asked in telephone interviews (CATI) about their attitudes to government spending and the federal government´s plans for the federal budget and the growth initiative. Respondents were selected using a multi-stage random sample as part of the forsa multi-topic survey (Politik-BUS), including landline and mobile phone numbers (dual-frame sample).Assessment of government spending on the following tasks (for health and care, defense, social affairs, climate protection, housing, integration of immigrants, pensions and internal security); if the government spends more money on one part of society, another part will automatically suffer vs. the whole of society benefits from it; general knowledge of the federal government´s plans for the 2025 federal budget (knows what the federal government has planned, has heard about it, but does not know any details, has not yet heard about it); assessment of the agreement on the 2025 federal budget; knowledge of specific plans in connection with the 2025 federal budget (compliance with the debt brake, higher spending on defense, more money for security authorities and 1. 000 new jobs in the federal police force, federal states to receive more money for childcare and support for schoolchildren in difficult social environments, more money for social housing, loans for Deutsche Bahn to invest in busy routes and outdated railroad stations); assessment of these plans as rather good or rather bad; level of knowledge of the planned growth initiative for more economic growth; assessment of the growth initiative; knowledge of concrete plans in connection with the growth initiative (more incentives to work with the citizen´s income and more sanctions for those who refuse reasonable work, tax benefits in the first three years for skilled workers from abroad who come to Germany, people who are still working at retirement age should be subsidized with bonuses, no more taxes and social security contributions on overtime bonuses, refugees should receive a work permit unbureaucratically and more quickly). Demography: sex; age (grouped); employment; education; party preference in the next federal election, voting behavior in the last federal election; federal state; income situation low, medium, high (net equivalent income); city size. Additionally coded were: Serial number; region west/east; weighting factor.Die Kurzumfrage zum Bundeshaushalt wurde von forsa im Auftrag des Presse- und Informationsamtes der Bundesregierung durchgeführt. Im Erhebungszeitraum 18.07.2024 bis 22.07.2024 wurde die deutschsprachige Bevölkerung ab 14 Jahren in Privathaushalten in telefonischen Interviews (CATI) zu ihren Einstellungen zu Staatsausgaben und den Plänen der Bundesregierung für den Bundeshaushalt und die Wachstumsinitiative befragt. Die Auswahl der Befragten erfolgte durch eine mehrstufige Zufallsstichprobe im Rahmen der forsa-Mehrthemenumfrage (Politik-BUS) unter Einschluss von Festnetz- und Mobilfunknummern (Dual-Frame Stichprobe).Bewertung der Staatsausgaben für die folgenden Aufgaben (für Gesundheit und Pflege, Verteidigung, Soziales, Klimaschutz, Wohnungsbau, Integration von Zugewanderten, Renten und innere Sicherheit); wenn der Staat für einen Teil der Gesellschaft mehr Geld ausgibt, wird automatisch ein anderer Teil darunter leiden vs. die ganze Gesellschaft profitiert davon; allgemeiner Kenntnisstand zu den Plänen der Bundesregierung für den Bundeshaushalt 2025 (weiß, was die Bundesregierung geplant hat, habe davon gehört, weiß aber keine Details, habe davon noch nicht gehört); Bewertung der Einigung zum Bundeshaushalt 2025; Kenntnisstand zu konkreten Plänen im Zusammenhang mit dem Bundeshaushalt 2025 (Einhalten der Schuldenbremse, höhere Ausgaben für Verteidigung, mehr Geld für Sicherheitsbehörden und 1.000 neue Stellen bei der Bundespolizei, Bundesländer sollen mehr Geld für Kinderbetreuung und die Förderung von Schulkindern in schwierigen sozialen Umfeldern bekommen, mehr Geld für den sozialen Wohnungsbau, Darlehen für die Deutsche Bahn, um in vielbefahrene Strecken und veraltete Bahnhöfe zu investieren); Bewertung dieser Vorhaben als eher gut oder eher schlecht; Kenntnisstand zur geplanten Wachstumsinitiative für mehr Wirtschaftswachstum; Bewertung der Wachstumsinitiative; Kenntnis von konkreten Plänen im Zusammenhang mit der Wachstumsinitiative (mehr Anreize beim Bürgergeld zum Arbeiten und mehr Sanktionen für diejenigen, die eine zumutbare Arbeit ablehnen, Steuervorteile in den ersten drei Jahren für Fachkräfte aus dem Ausland, die nach Deutschland kommen, Menschen, die im Rentenalter noch arbeiten, sollten mit Prämien bezuschusst werden, keine Steuern und Sozialversicherungsbeiträge mehr auf Zuschläge für Überstunden, Geflüchtete sollen unbürokratisch und schneller eine Arbeitserlaubnis erhalten). Demographie: Geschlecht; Alter (gruppiert); Erwerbstätigkeit; Bildung; Parteipräferenz bei der nächsten Bundestagswahl, Wahlverhalten bei der letzten Bundestagswahl; Bundesland; Einkommenslage niedrig, mittel, hoch (Nettoäquivalenzeinkommen); Ortsgröße. Zusätzlich verkodet wurde: Seriennummer; Region West/Ost; Gewichtungsfaktor