Liebe Kolleg:innen,
ich möchte Sie gerne auf das diesjährige DataFest Germany aufmerksam machen, das wir am 5.-7. April 2024 an der Universität Mannheim organisieren. Zielgruppe des DataFests sind Bachelor- und Masterstudierende aller Fachrichtungen.
Ich wäre Ihnen dankbar, wenn Sie die untenstehende Einladung an Ihre Studierenden weiterleiten würden.
Viele Grüße
Alexander Wenz
-
*English version below*
Liebe Studierende,
macht mit beim DataFest Germany 2024 am 5.-7. April 2024 @Universität Mannheim!
Das DataFest ist ein Studierenden-Wettbewerb zur Datenauswertung ("Hackathon"), an dem Bachelor- und Masterstudierende aller Fachrichtungen teilnehmen können. In Teams von 2-5 Personen analysiert ihr ein Wochenende lang einen großen und komplexen Datensatz. Ziel ist es, die besten Erkenntnisse zu gewinnen.
Das DataFest bietet euch die Möglichkeit, Daten mit eigenen kreativen Ideen auszuwerten, mit Expert*innen aus der Arbeitswelt und aus der Forschung in Kontakt zu treten und euch im Wettstreit um Preise, Ruhm und Ehre mit anderen Studierenden zu messen. Über das gesamte Wochenende sorgen wir für die Verpflegung.
Alle Infos zum DataFest Germany 2024 und die Anmeldung findet ihr unter www.datafest.de<http://www.datafest.de>. Die Anmeldefrist ist 15. März 2024.
Wir freuen uns auf euch!
Das DataFest Germany 2024 Organisationsteam
-
Dear students,
Join DataFest Germany 2024 on April 5-7, 2024 @University of Mannheim!
The DataFest is a student competition for data analysis ("hackathon") in which Bachelor and Master students of all disciplines can participate. In teams of 2-5 people, you analyze a large and complex data set over a weekend with the aim of gaining the best insights.
The DataFest offers you the opportunity to analyze data with your own creative ideas, get in touch with experts from industry and academia, and compete with other students for prizes, fame, and honor. Food and drinks will be provided throughout the weekend.
All information about DataFest Germany 2024 and registration can be found at www.datafest.de<http://www.datafest.de>. The registration deadline is March 15, 2024.
We look forward to seeing you!
The DataFest Germany 2024 organization team
Werte Kolleginnen und Kollegen,
wir möchten Sie nochmals auf die Session "Studying immigrants using the ESS: Methodological challenges, empirical consequences" auf der ESS Conference 2024 in Lissabon aufmerksam machen, die Antje Röder und ich gemeinsam organisieren. Reichen Sie Ihr Vortragsangebot bis zum 31. Januar 2024 ein. Wir freuen uns darauf!
Beste Grüße
Stephanie Müssig und Antje Röder
Studying immigrants using the ESS: Methodological challenges, empirical consequences, ESS Conference 2024 in Lisbon
Since its release, scholars from various disciplines all around the world use the ESS as source for research on persons with immigrant background. An important reason for its popularity among immigrant researchers is its bi-annual repetition and the regular participation of many Western European countries that both allow to combine data of several rounds and/or countries, resulting in a decent number of respondents with immigrant background. This circumvents the problem of small numbers that researchers usually face when using population survey data for studying immigrants. Moreover, its broad range of questions on (political) attitudes and behaviour is extra-ordinary for a multi-themed population survey, making the ESS often the only data source for studying these topics on immigrants or groups that mainly are of immigrant background, such as Muslims.
At the same time, there are reasons for reservations regarding its authoritative use on immigrants. Although the ESS displays a strong awareness for the need of research on immigrants by including items that enable their identification among respondents, it is not an immigrant survey. There is no specific sampling strategy for immigrant groups, and the questionnaire is only presented in a limited set of languages- a major obstacle for the participation of new immigrants or of immigrants with little knowledge of these languages. For this reason, non-response among immigrants is probably higher than among other population groups and not at random, which is considered a severe challenge to obtain unbiased results.
Although these and other sources for potential biases are well known among scholars, they have been neither systematically investigated nor frequently addressed in publications using the ESS. Among the open questions are: how biased is immigrant data really, and to what extent are substantial results affected by this? How can we take this into account in our analyses and when interpreting the results?
We encourage contributions with methodological focus (with or without comparative approach) that, e.g.,
* take stock of the descriptive representation of immigrants in the ESS
* assess whether bias in descriptive representation leads to bias in the substantive results on attitudes and behaviour
* appraise how the transition to a self-completion survey aggravates or alleviates existing caveats regarding research of immigrants with the ESS, and how to solve potential problems and pitfalls
* address other methodological issues regarding research on immigrants with the ESS
* use ESS data to study immigrants in an innovative way to overcome methodological challenges.
We invite abstract submissions via the ESS management platform ConfTool (max. 500 words). For submissions, please click here.<https://www.conftool.net/ess2024/>
The deadline for submissions is 31 January 2024.
For more information about the conference and its sessions, please click here: 5th International European Social Survey (ESS) Conference<https://europeansocialsurvey.org/about/ess-conference/5th-international-ess…>
For questions regarding the session "Studying immigrants using the ESS", please contact the session convenors Stephanie Müssig<mailto:stephanie.muessig@fau.de> and Antje Röder<mailto:roeder@staff.uni-marburg.de>.
+++
Dr. Stephanie Müssig
Stv. Geschäftsführerin - FAU EZIRE
Friedrich-Alexander-Universität Erlangen-Nürnberg
FAU Forschungszentrum Islam und Recht in Europa FAU EZIRE
Bohlenplatz 6 | 91054 Erlangen | Tel: +49 9131 85-26830 | Fax: +49 9131 85-26399
FAU Forschungszentrum FAU EZIRE<http://FAU%20Forschungszentrum%20FAU%20EZIRE> | www.ezire.fau.de/person/stephanie-muessig/<http://www.ezire.fau.de/person/stephanie-muessig/>
Dear colleagues,
Please consider submitting an abstract to the Sunbelt 2024 organized
session "Big data and field research in the study of social networks".
Please find further information below.
link to conference webpage: https://sunbelt2024.com/
For any questions, please feel free to contact me or Nikolitsa!
We look forward to meeting you in Edinburgh!
All best,
Betina
*
*
*Big data and field research in the study of social networks*
**
One of the major promises of “big data” was the ability to understand
how social networks emerge, operate, and shape human behavior on a much
larger scale than previously possible. Researchers have used large-scale
network data to generate new insights on topics as varied as network
evolution (Kossinets and Watts 2006), well-being (Jaidka et al. 2020),
and political misinformation (Guess, Nyhan, and Reifler 2020), among
many others. But researchers have become increasingly cognizant of the
limits of “big data” analyses, which may include sampling bias in the
data, confounds in the algorithms needed to uncover patterns, and weak
construct validity (boyd and Crawford 2012; Lazer et al. 2014). An
important response has been to address the limits of the data themselves
by employing mixed- or multi-methods approaches that capitalize on the
strengths of traditional social science methods, such as surveys,
experiments, or various qualitative methods (Bail et al. 2020; Gilbert
and Karahalios 2009; Grigoropoulou and Small 2022; Scharkow et al. 2020).
This organized session aims to host paper presentations on research in
social networks that combine different types of data and methods.
Critical reviews discussing specific methodological problems in
large-scale network data and how they can be addressed with field
research are also welcome.
*Organizers:*Nikolitsa Grigoropoulou, University of Bremen,
grigorop(a)uni-bremen.de
Betina Hollstein, University of Bremen, betina.hollstein(a)uni-bremen.de
--
Prof. Dr. Betina Hollstein
University of Bremen
Professor of Microsociology and Qualitative Methods
Research Data Center QUALISERVICE, head:https://www.qualiservice.org/en/
NEU - Interview zum FDZ Qualiservice:https://blog.bildungsserver.de/qualitative-forschungsdaten-sind-ein-schatz-der-gerade-erst-gehoben-wird/
SOCIUM - Research Center on Inequality and Social Policy
Dept. Methods Research/ Head
Dept. Life Course, Life Course Policy and Social Integration
Mary-Somerville-Str. 9, R. 9.3090 , D - 28359 Bremen
tel +49 (0)421-218-58512
e-mail:betina.hollstein@uni-bremen.de
http://www.socium.uni-bremen.de/about-the-socium/members/betina-hollstein/e…
Sekr.: Patricia Tegeler-Winde, tel.: +49 (0)421-218-58638. E-Mail:p.tegeler-winde@uni-bremen.de
Recent publications:
* Settersten, R.A., B. Hollstein, K.K. McElvaine (2024): ”Unlinked lives”: Elaboration of a concept and its significance for the life course. Advances in Life Course Research, Vol. 59, 100583 doi.org/10.1016/j.alcr.2023.100583
* Hollstein, B. (2024): Qualitative and Mixed Methods. In: J.McLevey, P. Carrington & J. Scott (Eds.): SAGE Handbook of Social Network Analysis, 2nd edition. Sage, 562-574.
* Hollstein, B. (2023): Personal Network Dynamics across the Life Course. A Relationship-related Structural Approach. Advances in Life Course Research. Vol 58, 100567. doi.org/10.1016/j.alcr.2023.100567
* Marsden, P.V. & B. Hollstein (2022): Advances and Innovations in Methods for Collecting Egocentric Network Data. Social Science Research 108, 102816.https://doi.org/10.1016/j.ssresearch.2022.102816
* Hollstein, B. (2021): Promises and Pitfalls of Qualitative Longitudinal Research. Longitudinal and Life Course Studies 12 (1), 7-17.https://doi.org/10.1332/175795920X16040851984946
* Hollstein, B. (2021): Georg Simmel’s Contribution to Social Network Research. In: M.L. Small, B.L. Perry, B. Pescosolido, & E. Smith (Eds.): Personal Networks: Classic Readings and New Directions in Ego-centric Analysis. New York: Cambridge University Press, 51-69.https://doi.org/10.1017/9781108878296.003
* Hollstein, B., R. Greshoff, U. Schimank & A. Weiss (2021) (Eds.): Soziologie - Sociology in the German speaking world. Special Issue Soziologische Revue 2020. De Gruyter: Berlin. 557 pages.https://doi.org/10.1515/9783110627275
Liebe Kolleg:innen,
ich möchte Sie gerne auf den folgenden Call for Item Submission im GESIS Panel Population Sample hinweisen.
Mit dem aktuellen Call for Item Submission: Perspectives on Europe werden sog. Short Submissions (≈1 Min Survey Zeit, längsschnittliche Wiederholungen sind möglich) eingeladen. Der Call greift die 10. EU-Parlamentswahlen auf und Einreichungen können sich auf Themen wie politische Einstellungen und Partizipation, Wahlverhalten, oder politisches Krisenbewusstsein und Zugehörigkeitsgefühl beziehen. Submission Deadline ist der 18. Februar.
Das GESIS Panel Population Sample erhebt Quer- und Längsschnittdaten in einem Mixed-Mode-Panel. Die probabilistische Stichprobe umfasst ca. 5.000 Personen, die alle drei Monate zu verschiedenen Themen befragt werden. Forschende haben die Möglichkeit Items zur Datenerhebung einzureichen, und so hoch-qualitative Daten kostenfrei zu erheben. Die GESIS Panel Daten umfassen bisher knapp 50 Wellen.
Darüber hinaus möchte ich Sie darauf aufmerksam machen, dass Itemeinreichungen ohne vorgegebene thematische Schwerpunktsetzung auch unabhängig des Calls laufend möglich sind. Informieren Sie sich dazu gerne auf der Webseite des GESIS Panels<https://www.gesis.org/en/gesis-panel/gesis-panel-home>.
Beste Grüße
Bernd Weiß
--
Dr. Bernd Weiß | Head of Team GESIS Panel
http://berndweiss.net/
GESIS - Leibniz Institute for the Social Sciences
P.O. Box 12 21 55 | 68159 Mannheim | Germany
Phone +49 621 1246 557 | Fax +49 621 1246 577
For further information follow us on:
Our website: http://www.gesis-panel.org/
On Facebook: https://www.facebook.com/GESISPanel
On Twitter: https://twitter.com/GESIS_Panel
On Instagram: https://www.instagram.com/gesis_panel/?hl=de
Stay up to date with our GESIS Panel Newsletter: https://www.gesis.org/gesis-panel/newsletter
Dear list members,
Please find below a reminder for the Special Issue CfP “Advances in survey sampling with social media advertisements”. Please note that the deadline for extended abstracts has been extended to February 9, 2024. Full papers will be due in Fall 2024.
*** Apologies for cross-posting ***
*** Abstract submission deadline extended to February 9, 2024 ***
Call for Papers: Special Issue in International Journal of Social Research Methodology<https://www.tandfonline.com/journals/tsrm20>
Advances in survey sampling with social media advertisements
Guest editors: Steffen Pötzschke<https://www.gesis.org/en/institute/staff/person/steffen.poetzschke>a, Michael Zoorob<https://michaelzoorob.com/about/>b, Bernd Weiß<https://www.gesis.org/en/institute/staff/person/bernd.weiss>a
aGESIS – Leibniz Institute for the Social Science , bMeta Platforms
We invite paper submissions on “Advances in survey sampling with social media advertisements” for a tentatively approved special issue in the International Journal of Social Research Methodology<https://www.tandfonline.com/journals/tsrm20> (IJSRM).
Survey sampling with social media advertisements was virtually non-existent a decade ago, but it has been increasingly adopted in recent years, especially for otherwise hard-to-reach populations. The increasing use of the approach warrants a more systematic review of its methodological particularities, advantages, disadvantages, and challenges; as well as practical and theoretical knowledge sharing of best practices using this method.
Submissions to the issue will either (a) describe empirical research that samples via social media advertising and sheds light on relevant methodological questions or (b) make novel theoretical or methodological contributions. Please note that the call is not limited to research using a specific social media platform.
Possible topics include, but are not limited to, the following:
● Discussion of suitable/innovative use cases (e.g., surveying otherwise hard-to-reach populations),
● Comparing social media recruited samples to external benchmarks or to one another,
● Strategies for measuring and mitigating bias,
● Influence of different features of ad campaigns – such as campaign optimization strategies, campaign length, audience targeting, ad placements, text, and images/video – on the cost and sample composition of social media recruited samples,
● Use of AI-based optimization features (such as lookalike audiences and automated A/B testing) and their impact on the survey process and sample composition,
● Use of advertisements in combination with chatbots, messenger services or survey apps,
● Role and impact of the design decisions taken regarding features comparable to “classic” survey design elements (e.g., wording of advertisements in their function as survey invitation),
● Impact and management of other contextual factors – such as user comments on advertisements, the advertiser’s identity or timing of the survey,
● Ethical and data privacy considerations, and
● Insights from social media survey sampling about social media platform algorithms or survey research methods more broadly.
Please submit extended abstracts (a maximum of 1000 words), along with co-authors and affiliations, to ad-sampling-si(a)gesis.org<mailto:ad-sampling-si@gesis.org> by February 9, 2024. We anticipate providing feedback on acceptance in Spring 2024. Please note that full papers will have to be submitted in Fall 2024 (see timeline below).
Please note that IJSRM has a two-stage submission process for Special Issues<https://files.taylorandfrancis.com/TSRM_SpecialIssue_Guidelines.pdf>. After an initial review and expression of interest in the Special Issue proposal, the journal’s editors have invited us to submit a Stage 2 proposal.
Reviewing process
The Special Issue will apply a multi-stage reviewing process. First, the submission of an extended abstract (maximum of 1,000 words) is required. These extended abstracts are mandatory and serve as a basis for the guest editors to decide on the inclusion of individual papers in the Stage 2 submission to the journal. After the positive review of the Special Issue Stage 2 submission by the journal’s editors, authors are invited to submit a full paper which will be subject to peer-review with at least two experts in the field.
Timeline (revised)
* October 25, 2023: Call for Papers issued
* New Deadline - February 9, 2024: Extended abstracts due
* February 26, 2024: Authors are informed by SI editors about inclusion of their abstract in Stage 2 submission to the journal
* March 1, 2024: SI editors submit Stage 2 SI proposal to journal (including the extended abstracts of all selected papers)
* Spring 2024: Upon final acceptance of the Special Issue, authors receive feedback on their paper proposals and an invitation to submit a full paper. Full papers will be due for submission six months after this date.
Please direct any questions to ad-sampling-si(a)gesis.or<mailto:ad-sampling-si@gesis.org>g<mailto:ad-sampling-si@gesis.org>
Find this CfP online: https://www.gesis.org/en/gesis-panel/gesis-panel-home/calls
Liebe Kolleg*innen in der Methoden-Sektion,
das diesjährige Spring Seminar ist beinahe ausgebucht. In Woche 2 und 3 gibt es jeweils noch einige wenige Plätze. Wie immer gilt: First come, first served!
Programm, Termine und Links zu weiteren Infos und der Registrierung auf unseren Seiten: Siehe unten.
Viele Grüße,
Sebastian
***Apologies for cross-posting***
Dear colleagues,
There are just few places left in two of three courses at this year's GESIS Spring Seminar! There is no registration deadline; places are allocated on a first-come, first-served basis.
The Spring Seminar offers high-quality training in state-of-the-art techniques in quantitative data analysis taught by leading experts in the field. It is designed for advanced graduate or PhD students, post-docs, as well as junior and senior researchers. In 2024, all courses will deal with "Recent Developments in Longitudinal Data Analysis" in the social sciences and beyond.
Extensive hands-on exercises and tutorials complement lectures in each course. The Spring Seminar will take place onsite at GESIS Cologne, Germany, from 26 February to 15 March 2024.
For registration and detailed course descriptions, please visit www.gesis.org/springseminar<http://www.gesis.org/springseminar>.
GESIS Spring Seminar 2024 Program:
Week 1 (26 February - 01 March) [fully booked; we are operating a waiting list]
Modern Longitudinal Analysis Using R<https://training.gesis.org/?site=pDetails&child=full&pID=0x0CA8F929E23A4BB2…>
Alexandru Cernat, Nick Shryane
Week 2 (04 - 08 March) [few places left]
Recent Developments in Difference-in Differences Estimation<https://training.gesis.org/?site=pDetails&child=full&pID=0x0CA8F929E23A4BB2…>
Scott Cunningham
Week 3 (11 - 15 March) [few places left]
Causal Machine Learning for Cross-sectional and Panel Data<https://training.gesis.org/?site=pDetails&child=full&pID=0x0CA8F929E23A4BB2…>
Martin Spindler, Jannis Kück
Courses must be booked separately - whether you wish to attend one, two, or all three. There is no registration deadline, but places are limited and allocated on a first-come, first-served basis. Thanks to our cooperation with the Cologne Graduate School in Management, Economics, and Social Sciences at the University of Cologne, enrolled doctoral students can obtain three ECTS credit points<https://www.gesis.org/en/gesis-training/what-we-offer/spring-seminar-cuttin…> per one-week course.
For workshops (onsite or online) on related and other social science research methods, please visit www.gesis.org/workshops<http://www.gesis.org/workshops>.
We would appreciate you forwarding this announcement to other potentially interested parties.
Thank you, and best wishes,
Your GESIS Training team
---
GESIS - Leibniz Institute for the Social Sciences
email: training(a)gesis.org<mailto:training@gesis.org>
web: www.gesis.org/training<http://www.gesis.org/training>
X: https://twitter.com/gesistraining
facebook: https://www.facebook.com/GESISTraining
--
Dr. Sebastian E. Wenz
Senior Researcher
GESIS - Leibniz Institute for the Social Sciences
Phone: +49 221-47694-159
www.gesis.org/training<http://www.gesis.org/training>
Liebe Kolleginnen und Kollegen,
2024 startet unsere großangelegte Panelstudie GLEN (German Longitudinal Environmental Study) als ein von der DFG gefördertes Langzeitprojekt. Ziel des Kooperationsprojekts der Universität Kaiserslautern, der Universität Leipzig und der LMU München ist die Erhebung hochwertiger Längsschnittdaten zu Umweltverhalten, Umwelteinstellungen, Akzeptanz politischer Maßnahmen und Umweltungleichheit. Wir planen die Daten nutzerfreundlich aufbereitet als Scientific-Use-File der wissenschaftlichen Fachöffentlichkeit bereitzustellen. Mit GLEN wollen wir die Sozialwissenschaften als festen Bestandteil in die Klima- und Umweltforschung integrieren und damit den „Faktor Mensch“ bei Fragen des Umwelt- und Klimaschutzes ins Zentrum rücken.
Demnächst suchen wir für den Standort Kaiserslautern eine:n wissenschaftliche Mitarbeiterin oder Mitarbeiter (m/w/d) als Postdoc im Bereich Regionalisierung / Georeferenzierte Daten.
https://www.b-ite.com/recruitingmanager/job-postings/share/zF7VQTLy7oCUmpDS…
Die Ausschreibefrist wurde verlängert!
Viele Grüße,
Henning Best
* German version below/Deutsche Version weiter unten *
Our online series "Meet the Experts" starts the new year with a new season on "Knowledge technologies for the Social Sciences: Access to Social Science Data and Services"!
We start by investigating social scientists' information-seeking behavior and data needs, which form the basis for suitable search infrastructures and knowledge graphs to make social science data and information findable, accessible, and reusable. Building on this, we show what opportunities and challenges emerge from the adoption of technological advances in the social sciences, such as large language models and novel data sources mined from the Web. We will conclude with a presentation on the automatic extraction of scientific information from scholarly texts, which helps to improve search and understanding of research information and their dependencies.
Here are the dates of the one-hour online talks (on Thursdays, 1-2 pm):
· 18.01.2024: Understanding the information-seeking behavior of social scientists (Dr. Dagmar Kern)
· 15.02.2024: Five ways to turn your dataset into click bait (Dr. Brigitte Mathiak)
· 14.03.2024: Searching the social sciences with GESIS Search (Dr. Daniel Hienert)
· 11.04.2024: How knowledge graphs can help you to share research data and information (Dr. Benjamin Zapilko & Debanjali Biswas)
· 16.05.2024: Opportunities and challenges of Large Language Models for the social sciences (Dr. Dimitar Dimitrov & Dr. Hajira Jabeen)
· 13.06.2024: Preserving and analysing large-scale Twitter data (Dr. Dimitar Dimitrov)
· 11.07.2024: Introduction to scholarly information extraction (Wolfgang Otto, Dr. Lu Gan, Dr. Saurav Karmakar, & Dr. Philipp Mayr)
After the presentation, our experts will be available for further discussion and to answer questions.
You can find the registration and further information about the talks here: https://www.gesis.org/en/services/sharing-knowledge/meet-the-experts
We are looking forward to seeing you at the talks!
Cornelia Neuert, on behalf of the GESIS Meet-the-Expert team
***
Deutsch
Unsere Online-Reihe “Meet the Experts“ startet mit einer neuen Staffel zu „Knowledge technologies for the Social Sciences: Access to Social Science Data and Services“ ins neue Jahr!
Wir beginnen mit der Untersuchung des Informationssuchverhaltens und der Datenbedürfnisse von Sozialwissenschaftler*innen, die die Grundlage für geeignete Suchinfrastrukturen und Wissensgraphen bilden, um sozialwissenschaftliche Daten und Informationen auffindbar, zugänglich und wiederverwendbar zu machen. Darauf aufbauend zeigen wir, welche Möglichkeiten und Herausforderungen sich aus der Übernahme technologischer Fortschritte in den Sozialwissenschaften ergeben, wie z. B. große Sprachmodelle und neuartige Datenquellen aus dem Web. Abschließend wird die automatische Extraktion wissenschaftlicher Informationen aus wissenschaftlichen Texten vorgestellt, die dazu beiträgt, die Suche und das Verständnis von Forschungsinformationen zu verbessern.
Termine der jeweils einstündigen englischsprachigen Online-Vorträge (donnerstags, 13:00 – 14:00 Uhr):
· 18.01.2024: Understanding the information-seeking behavior of social scientists (Dr. Dagmar Kern)
· 15.02.2024: Five ways to turn your dataset into click bait (Dr. Brigitte Mathiak)
· 14.03.2024: Searching the social sciences with GESIS Search (Dr. Daniel Hienert)
· 11.04.2024: How knowledge graphs can help you to share research data and information (Dr. Benjamin Zapilko & Debanjali Biswas)
· 16.05.2024: Opportunities and challenges of Large Language Models for the social sciences (Dr. Dimitar Dimitrov & Dr. Hajira Jabeen)
· 13.06.2024: Preserving and analysing large-scale Twitter data (Dr. Dimitar Dimitrov)
· 11.07.2024: Introduction to scholarly information extraction (Wolfgang Otto, Dr. Lu Gan, Dr. Saurav Karmakar, & Dr. Philipp Mayr)
Nach einem Vortrag zu dem jeweiligen Thema stehen Ihnen unsere Expert*innen jeweils für Fragen und Diskussion zur Verfügung.
Die Anmeldung und weitere Informationen zu den Vorträgen finden Sie hier: https://www.gesis.org/angebot/wissen-vermitteln/meet-the-experts
Wir freuen uns, Sie begrüßen zu können!
Cornelia Neuert
---------------------------
Dr. Cornelia Neuert
GESIS – Leibniz Institute for the Social Sciences
Survey Design & Methodology | Questionnaire Design & Evaluation
P.O. Box 12 21 55 | 68072 Mannheim |Germany
Phone: +49 (0)621 1246-225 | Fax: +49 (0)621 1246-100
Email: cornelia.neuert(a)gesis.org<mailto:cornelia.neuert@gesis.org>
www.gesis.org<http://www.gesis.org/>