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COINS: Mathematik-Gesamtdatensatz (Schweiz & Deutschland)
No full textDas Projekt knüpft an die Erkenntnisse aus dem SNF-Projekt zur „Instruktionssensitivität von Testitems in der Pädagogisch-Psychologischen Diagnostik“ (2015 bis 2019) an. Während es im ersten Projekt (Daten ebenfalls über SWISSUbase verfügbar, Ref. 13160) um die Frage der Messung der Instruktionssensitivität von Testitems ging, steht in diesem SNF-Projekt die Konstruktion instruktionssensitiver Testitems im Fokus. Wie lassen sich instruktionssensitive Testitems konstruieren? Im Rahmen des neuen SNF-Projekts zur Konstruktion instruktionssensitiver Testitems steht die Identifizierung von Itemmerkmalen im Fokus, welche die Instruktionssensitivität von Testitems bedingen. Was unterscheiden instruktionssensitive Items von nicht instruktionssensitiven Items? Für die Bearbeitung dieser Fragestellung sollen in einem ersten Schritt Itemmerkmale mithilfe von Mathematik-Expertinnen und -Experten identifiziert werden. In einem zweiten Schritt erfolgt die empirische Überprüfung der identifizierten Itemmerkmale anhand von Leistungsdaten der Schülerinnen und Schüler sowie Daten zum Unterricht. Erkenntnisse darüber, welche Itemmerkmale die Instruktionssensitivität von Testitems bedingen, ist für eine ökonomische Erstellung neuer instruktionssensitiver Tests bzw. Testitems von grossem Wert. Die Ergebnisse richten sich insbesondere an Interessierte aus der empirischen Bildungsforschung und der pädagogischen Psychologie. Das binationale Forschungsprojekt ist an der Pädagogischen Hochschule St.Gallen (Prof. Dr. Jan Hochweber, Dr. Stephanie Leininger und Dr. Stephan Schönenberger) und am DIPF | Leibniz-Institut für Bildungsforschung und Bildungsinformation in Frankfurt a. M. (Prof. Dr. Johannes Hartig, Dr. Marit Kristine List und Dr. Alexander Naumann) verortet. Prof. Dr. Maria Araceli Ruiz-Primo von der Stanford University und Stephan Schönenberger von der Pädagogischen Hochschule Thurgau / Pädagogischen Hochschule St. Gallen sind offizielle Kooperationspartner und werden mit ihrer fachlichen Expertise im Bereich der Test- und Itemkonstruktion wesentlich zur erfolgreichen Umsetzung des Projekts beitragen.The project builds on the findings of the SNSF project "Instructional Sensitivity of Test Items in Educational Testing" (2015 to 2019). While the first project dealt with the question of how to measure the instructional sensitivity of test items, the new SNSF project focuses on the construction of instructionally sensitive test items. How can instructionally sensitive test items be constructed? The SNSF project on the construction of instructionally sensitive test items focuses on the identification of item characteristics that determine the instructional sensitivity of test items. What distinguishes instructionally sensitive test items from test items which are not? In a first step, potentially relevant item characteristics will be identified with the help of mathematics experts. In a second step, the identified item characteristics’ relationship to instructional sensitivity will be empirically tested using student performance data and teaching data. Findings about which item characteristics determine the instructional sensitivity of test items are of great value for the economical construction of new instructionally sensitive tests or test items. The results are particularly aimed at interested parties from empirical educational research and educational psychology. The binational research project is conducted at St.Gallen University of Teacher Education (Prof. Dr. Jan Hochweber, Dr. Stephanie Leininger, and Prof. Dr. Stephan Schönenberger) and at the DIPF | Leibniz Institute for Research and Information in Education in Frankfurt a. M. (Prof. Dr. Johannes Hartig, Dr. Marit Kristine List, and Dr. Alexander Naumann). Prof. Dr. Maria Araceli Ruiz-Primo from Stanford University is an official cooperation partner and will contribute significantly to the successful implementation of the project with her professional expertise in the field of test and item construction
Surface Groups Western Sahara 1984-2021
No full textThis project develops a novel procedure for proxying economic activity with daytime satellite imagery across time periods and spatial units, for which reliable data on economic activity are otherwise not available. In developing this unique proxy, we apply machine-learning techniques to a historical time series of daytime satellite imagery from the Landsat program dating back to 1984. Compared to satellite data on night light intensity, another common economic proxy, our proxy more precisely predicts economic activity at smaller regional levels and over longer time horizons. Our procedure is generalizable to any region in the world, and it has great potential for analyzing historical economic developments, evaluating local policy reforms, and controlling for economic activity at highly disaggregated regional levels in econometric applications. Therefore, we produce our proxy for any region in the world and publish the data as georeferend TIF files in this repository. In our paper, we demonstrate our measure’s usefulness for the example of Germany, where East German data on economic activity are unavailable for detailed regional levels and historical time series
Surface Groups Guatemala 1984-2023
No full textThis project develops a novel procedure for proxying economic activity with daytime satellite imagery across time periods and spatial units, for which reliable data on economic activity are otherwise not available. In developing this unique proxy, we apply machine-learning techniques to a historical time series of daytime satellite imagery from the Landsat program dating back to 1984. Compared to satellite data on night light intensity, another common economic proxy, our proxy more precisely predicts economic activity at smaller regional levels and over longer time horizons. Our procedure is generalizable to any region in the world, and it has great potential for analyzing historical economic developments, evaluating local policy reforms, and controlling for economic activity at highly disaggregated regional levels in econometric applications. Therefore, we produce our proxy for any region in the world and publish the data as georeferend TIF files in this repository. In our paper, we demonstrate our measure’s usefulness for the example of Germany, where East German data on economic activity are unavailable for detailed regional levels and historical time series
Surface Groups Grenada 1984-2023
No full textThis project develops a novel procedure for proxying economic activity with daytime satellite imagery across time periods and spatial units, for which reliable data on economic activity are otherwise not available. In developing this unique proxy, we apply machine-learning techniques to a historical time series of daytime satellite imagery from the Landsat program dating back to 1984. Compared to satellite data on night light intensity, another common economic proxy, our proxy more precisely predicts economic activity at smaller regional levels and over longer time horizons. Our procedure is generalizable to any region in the world, and it has great potential for analyzing historical economic developments, evaluating local policy reforms, and controlling for economic activity at highly disaggregated regional levels in econometric applications. Therefore, we produce our proxy for any region in the world and publish the data as georeferend TIF files in this repository. In our paper, we demonstrate our measure’s usefulness for the example of Germany, where East German data on economic activity are unavailable for detailed regional levels and historical time series
National Maternity Experience Survey (NMES), 2020
No full textThe National Maternity Experience Survey 2020 invited women to share their experiences of Ireland’s maternity services. The survey is part of the National Care Experience Programme — a joint initiative by the Health Information and Quality Authority (HIQA), the Health Service Executive (HSE) and the Department of Health. The survey reflected a commitment made in The National Maternity Strategy 2016-2026 to evaluate maternity care services from the perspectives of the women who use them.6,357 women who gave birth in October and November 2019 were invited to participate, with 3,204 responding. The survey questionnaire contained 68 questions which capture the whole maternity pathway from antenatal care, through labour and birth, to postnatal care in the community. The aim of the survey was to learn from the experiences of women to improve the safety and quality of the care that they and their babies received. HIQA, the HSE and the Department of Health committed to acting on the findings of the National Maternity Experience Survey to improve the quality of maternity care services in Ireland
Sosiaalinen media työelämässä: organisaatiokysely 2018
No full textAineistossa kartoitetaan suomalaisten organisaatioiden työntekijöiden sosiaalisen median käyttöä työelämässä sekä heidän työhyvinvointiaan. Aluksi vastaajilta kysyttiin heidän yleisistä sosiaalisen median käyttötottumuksistaan, kuten kuinka usein he käyttävät eri sosiaalisen median palveluita ja mihin tarkoituksiin. Lisäksi selvitettiin, kuinka usein ja mihin tarkoituksiin vastaajat käyttävät sosiaalista mediaa työssään sekä millaisia kokemuksia sosiaalisen median työkäyttöön liittyy. Seuraavaksi kyselyssä käsiteltiin vastaajien kokemuksia sosiaalisen median aiheuttamasta stressistä ja kuormituksesta. Tämän jälkeen käsiteltiin työhyvinvointiin liittyviä teemoja, kuten työtyytyväisyyttä, työn imua ja organisaatioon identifioitumista. Lopuksi kartoitettiin vastaajien kokemuksia nettikiusaamisesta työpaikalla sekä heidän yleistä hyvinvointiaan ja työssä jaksamistaan. Kyselylomakkeen kokeellisessa osiossa vastaajat jaettiin satunnaisesti kahteen ryhmään. Vastaajien tuli kuvitella hakevansa uutta oman alansa työpaikkaa ja lukea lyhyt kuvaus avoinna olevasta tehtävästä. Tämän jälkeen he arvioivat työpaikkaa ilmoituksen perusteella kuuden väittämän avulla. Koeryhmä sai työpaikkailmoituksen, jossa korostettiin sosiaalisen median merkitystä työpaikan viestinnässä ja kontrolliryhmä sai ilmoituksen ilman viittausta sosiaaliseen mediaan. Kyselyssä on käytetty esimerkiksi seuraavia mittareita: Identity Bubble Reinforcement Scale IBRS (Samanmielisyys ja identiteettikuplat sosiaalisessa mediassa), Utrecht Work Engagement Scale UWES (Työn imu 9 -mittari), Maslach Burnout Indicator MBI-GS (Työuupumuskysely), General Health Questionnaire GHQ-12 (Psyykkinen kuormittuneisuus), Copenhagen Psychosocial Questionnaire CPSQII (Työn vaatimukset ja voimavarat) ja Cyberbullying Questionnaire CBQ (Nettikiusaaminen työpaikalla). Taustamuuttujina aineistossa ovat muun muassa vastaajien sukupuoli, syntymävuosi, siviilisääty, kotitalouden henkilömäärä, kotitaloudessa asuvien lasten lukumäärä, koulutustaso, ammattiasema, alaisten määrä, työaika ja bruttotulot kuukaudessa.The survey maps the use of social media in working life among employees of Finnish organisations, as well as their occupational well-being. First, respondents were asked about their general social media usage habits, including how frequently they use various platforms and for what purposes. In addition, the survey examined the frequency and purpose of social media use in the workplace, as well as respondents' experiences related to professional use of social media. Next, the survey addressed respondents' experiences of stress and strain caused by social media. This was followed by topics related to well-being at work, such as job satisfaction, work engagement, and organisational identification. Finally, the survey mapped the respondents' experiences of online bullying in the workplace, as well as their general well-being and coping at work. In the experimental part of the survey, respondents were randomly divided into two groups. They were asked to imagine applying for a new job in their field and to read a brief description of an open position. They then evaluated the position based on six statements. The experimental group received a job advertisement emphasizing the importance of social media in workplace communication, while the control group received an advertisement with no reference to social media. The survey included the following measurement instruments, among others: Identity Bubble Reinforcement Scale IBRS, Utrecht Work Engagement Scale UWES, Maslach Burnout Indicator MBI-GS, General Health Questionnaire GHQ-12, Copenhagen Psychosocial Questionnaire CPSQII, and Cyberbullying Questionnaire CBQ. Background variables include, among others, gender, year of birth, marital status, household size, number of children in the household, education level, occupational status, number of subordinates, working hours, and monthly gross income
TechnikRadar 2025 - Schwerpunkt Digitale Transformation und KI
No full textIm Fokus des TechnikRadar 2025 stehen neben den grundlegenden Einstellungen der Deutschen zu Technik ihre Einschätzungen im Hinblick auf Digitale Transformation und Künstliche Intelligenz: Sehen die Deutschen darin mehr Nutzen oder Risiken – für sich persönlich oder für die Gesellschaft? Wie wichtig sind ihnen Datenschutz, Komfort und Unabhängigkeit von wenigen großen Technologieunternehmen? Wie bewerten sie ihre Erfahrungen mit generativer KI? Und wie schätzen sie die Rolle der Forschung für die militärische Verteidigung ein? Das Projekt wird von der Carl-Zeiss-Stiftung gefördert. Die Ergebnisse des TechnikRadar 2025 basieren auf einer Online-Erhebung (CAWI) im Rahmen des forsa.omninet-Panels. Im Zeitraum vom 24.02.2025 - 12.03.2025 nahmen von 2,003 Personen teil. Die Grundgesamtheit der Befragung ist die deutschsprachige Wohnbevölkerung ab 16 Jahren in der Bundesrepublik Deutschland. Die Auswahl der Befragten erfolgte per Zufall aus dem forsa.omninet-Panel.Im Fokus des TechnikRadar 2025 stehen neben den grundlegenden Einstellungen der Deutschen zu Technik ihre Einschätzungen im Hinblick auf Digitale Transformation und Künstliche Intelligenz: Sehen die Deutschen darin mehr Nutzen oder Risiken – für sich persönlich oder für die Gesellschaft? Wie wichtig sind ihnen Datenschutz, Komfort und Unabhängigkeit von wenigen großen Technologieunternehmen? Wie bewerten sie ihre Erfahrungen mit generativer KI? Und wie schätzen sie die Rolle der Forschung für die militärische Verteidigung ein? Das Projekt wird von der Carl-Zeiss-Stiftung gefördert. Die Ergebnisse des TechnikRadar 2025 basieren auf einer Online-Erhebung (CAWI) im Rahmen des forsa.omninet-Panels. Im Zeitraum vom 24.02.2025 - 12.03.2025 nahmen von 2,003 Personen teil. Die Grundgesamtheit der Befragung ist die deutschsprachige Wohnbevölkerung ab 16 Jahren in der Bundesrepublik Deutschland. Die Auswahl der Befragten erfolgte per Zufall aus dem forsa.omninet-Panel
Replication files for: Asymmetric Backlash against Structural Economic Change: The Electoral Consequences of the Coal Phase-Out in Germany
No full textThe published R Scripts and Stata syntax files (do-files) and datasets (among which a partial version of the 2020 Inequality Barometer published under https://doi.org/10.7802/2740) can be used to replicate the results reported in the article (Stutzmann, 2025). Past research has often attributed electoral backlash to structural economic change to a lack of compensation and interest group representation for affected groups. Is that backlash then mitigated in contexts where both of these conditions are fulfilled? I argue that perceived economic deprivation fuelling political disengagement as well as disappointment with the issue-owning party are important factors contributing to such a backlash. Using the case of Germany, I empirically analyse the electoral repercussions of a coal phase-out in the presence of compensation for affected groups as well as active involvement of labour and business interests in political decision-making. By employing a series of staggered difference-in-differences models, I investigate whether the closures of coal plants and mines between 2007 and 2022 affected voting behaviour at the municipal level. I find that these closures resulted in an asymmetric backlash in the form of lower vote shares for the issue owner, the Social Democratic Party, and higher abstention rates in affected municipalities. With the significant politicisation around fossil fuel-based energy generation, these findings have important implications for the remaining coal phase-outs worldwide.The published R Scripts and Stata syntax files (do-files) and datasets (among which a partial version of the 2020 Inequality Barometer published under https://doi.org/10.7802/2740) can be used to replicate the results reported in the article (Stutzmann, 2025). Past research has often attributed electoral backlash to structural economic change to a lack of compensation and interest group representation for affected groups. Is that backlash then mitigated in contexts where both of these conditions are fulfilled? I argue that perceived economic deprivation fuelling political disengagement as well as disappointment with the issue-owning party are important factors contributing to such a backlash. Using the case of Germany, I empirically analyse the electoral repercussions of a coal phase-out in the presence of compensation for affected groups as well as active involvement of labour and business interests in political decision-making. By employing a series of staggered difference-in-differences models, I investigate whether the closures of coal plants and mines between 2007 and 2022 affected voting behaviour at the municipal level. I find that these closures resulted in an asymmetric backlash in the form of lower vote shares for the issue owner, the Social Democratic Party, and higher abstention rates in affected municipalities. With the significant politicisation around fossil fuel-based energy generation, these findings have important implications for the remaining coal phase-outs worldwide
Labour Force Survey Five-Quarter Longitudinal Dataset, July 2024 - September, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.Background The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation. Longitudinal data The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary. LFS Documentation The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2022 WeightingThe population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust.Main Topics:The five-quarter longitudinal datasets include a subset of the most commonly used variables from the Quarterly Labour Force Survey (QLFS), covering the main areas of the survey
Finnish Science Barometer 2024
No full textTutkimuksessa selvitettiin suomalaisten suhtautumista tieteeseen ja tutkimukseen sekä kartoitettiin niiden roolia yhteiskunnassa. Uutena teemana kysyttiin vastaajan suhtautumisesta tekoälyyn sekä sen soveltamiseen yhteiskunnassa. Aluksi tiedusteltiin, mistä tieteenaloista vastaaja on kiinnostunut sekä mistä tiedonlähteistä vastaaja saa tietoa tieteestä ja sen kehityksestä. Lisäksi kysyttiin tieteen ja tutkimuksen vaikutuksista ihmisten arkipäivään tulevaisuudessa sekä pyydettiin vastaajaa arvioimaan eri seikkoja liittyen tieteen ja tutkimuksen tilaan ja tasoon Suomessa. Tämän jälkeen kysyttiin luottamuksesta yhteiskunnan instituutioita sekä tiedettä ja tutkimusta kohtaan ja vastaajia pyydettiin nimeämään julkisuudessa esiintyvä tutkija, jota he pitävät luotettavana. Lisäksi tiedusteltiin tieteen ja tutkimuksen kehittymisestä sekä tieteen kyvystä ratkaista yhteiskunnallisia ongelmia. Vastaajilta kysyttiin myös tieteen ja yhteiskunnan sekä tieteen ja politiikan suhteesta. Edelleen kysyttiin tieteen suhteesta arkielämään ja omiin henkilökohtaisiin näkemyksiin. Lopuksi selvitettiin vastaajan suhtautumisesta tekoälyyn ja sen sovelluksiin, kuten itseajaviin autoihin tai kasvojentunnistukseen rajavalvonnassa. Viimeiseksi vastaaja sai pohtia tekoälyn tuomia mahdollisuuksia tai uhkia avoimessa kysymyksessä. Taustamuuttujina olivat muun muassa sukupuoli, ikä, asema, asuinkunnan koko, kuntaryhmitys ja suuralue, asumismuoto, talouden koko, koulutustietoja, puoluekanta ja talouden vuositulot.The survey studied Finnish public opinion on science and research and mapped their role in society. As a new theme, respondents were asked about their attitudes toward artificial intelligence and its applications in society. First, respondents were asked which scientific fields interested them and where they obtained information about science and its development. Respondents were also asked about the future impact of science and research on people's everyday lives, and to evaluate various aspects of the state and quality of science and research in Finland. Next, respondents were asked about their trust in various institutions, including the European Parliament, the church, trade unions, the media, the armed forces, and universities. The respondents were also asked to name a Finnish researcher whom they considered trustworthy. In addition, questions were asked about the development of science and research and the ability of science to solve societal problems. Respondents were also asked about the relation between science and politics. The survey also included various attitudinal statements about science and research. The statements covered, for instance, relationships between religion and science, science funding, alternative medicine, researchers' involvement in politics, use of scientific information in political decision-making, impact of scientific and technological development, climate change, and nutrition. Finally, the respondents' attitudes toward artificial intelligence and its applications, such as self-driving cars or facial recognition in border control, were examined. The respondents were also asked to consider the opportunities and threats posed by artificial intelligence in an open-ended question. Background variables included the respondent's gender, age, population of their municipality of residence, NUTS2 region, type of accommodation, household characteristics, basic and vocational education, statistical grouping of municipalities, political party preference, economic activity and occupational status, and household's annual income