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Antisemitische Einstellungen bei jungen Menschen in Deutschland. Befunde repräsentativer Umfragen zu Entwicklungen zwischen 2022 und 2024. UHH MOTRA Spotlight No. 13
No full textEs werden Ergebnisse aus zwei Erhebungswellen der bundesweit repräsentativen Befragungen vorgestellt, die im Rahmen der MOTRA-Studie "Junge Menschen in Deutschland" durchgeführt wurden. Diese zeigen für Jugendliche und Heranwachsende im Alter von 16 bis 21 Jahren erhebliche Anstiege tradierter Formen antisemitischer Einstellungen zwischen 2022 und 2024 . Solche signifikanten Zunahmen der sind bei allen Teilgruppen der jungen Menschenzu erkennen. Es fallen allerdings deutliche Unterschiede in Abhängigkeit von Religionszugehörigkeit und Migrationshintergrund auf.Bei nichtmuslimischen Migrantinnen und Migranten sind die Raten antisemitischer Einstellungen bei Personen der ersten Migrationsgeneration signifikant höher als bei den Angehörigen der zweiten Migrationsgeneration. Dies gilt sowohl 2022 als auch 2024. Für beiden Migrationsgenerationen zeigen sich auch deutliche Anstiege des Antisemitismus im Vergleich der beiden Jahrgänge. Bei jungen Musliminnen und Muslimen stellt sich die Lage anders dar. Hier kam es bei den Angehörigen der ersten Migrationsgeneration zu keinen Veränderungen der hohen Rate antisemitischer Einstellungen in dieser Zeit. Im Falle der zweiten Migrationsgeneration findet sich demgegenüber ein markanter Anstieg der Antisemitismusraten auf mehr als das Dreifache. Die stark ausgeprägten Zunahmen antisemitischer Einstellungen bei jungen Musliminnen und Muslimen der zweiten Migrationsgeneration verweisen auf Retraditionalisierungs- und Radikalisierungsprozesse, die hier in besonderem Maße stattgefunden haben.Dies wird gestützt durch Befunde die zeigen, dass in dieser Zeit auch eine verstärkte Hinwendungen zu fundamentalistischen, rigide-autoritären religiösen Orientierungen stattgefunden hat. Es liegt nahe, dass die besonders starken Anstiege des Antisemitismus bei jungen Musliminnen und Muslimen der zweiten Migrationsgeneration auch durch deren spezifische Wahrnehmungen des Gaza-Krieges und die Berichte über zivile Opfer unter der dort lebenden muslimischen Zivilbevölkerung mit beeinflusst worden sein können. Rigide Reaktionen auf israelkritische Proteste junger Menschen, die Opfer in der palästinensischen Zivilbevölkerung skandalisieren, u.a. deren Etikettierung als antisemitisch und kriminell, stehen gerade hier aus theoretischer Sicht in der Gefahr, Zunahmen des Antisemitismus zu befördern. Die Befunde werden mit Blick auf die Zielgruppen für die Antisemtismusprävention bei jungen Menschen in Deutschland diskutiert. Insoweit wird insbesondere ein kultursensibler Zugang zur Risikogruppe der mit Blick auf die Entwicklung antisemitischer Einstellungen besonders kritische Gruppe diskutiert.
Abstract:
Results of two representative surveys of people aged 16 to 21 years show significant increases of prevalence rates of traditional anti-Semitic attitudes between 2022 and 2024. According to the results of theses surveys anti-Semitic attitudes are significantly more prevalent among young Muslims compared to young Christians or those without religious affiliation. Among non-Muslim migrants, corresponding increases in anti-Semitic attitudes have been observed in both first- and second-generation migrants, with first-generation respondents being significantly more likely to hold such views than their second-generation counterparts. Among first-generation young Muslims, there were virtually no changes in their high rates of anti-Semitic attitudes between 2022 and 2024. However, among second-generation young Muslims, there were considerable increases, resulting in the rates of anti-Semitic attitudes between the two generations being nearly indistinguishable by 2024.
This rise in anti-Semitic attitudes among second-generation young Muslims can be explained as a result of retraditionalization and radicalization processeses that are accompanied with shifts towards more fundamental religious orientations that can be observed among young muslims in Germany. It is reasonable to assume that this trend among young Muslims is particularly fueled by the ongoing conflict in the Middle East, particularly the Gaza War, as well as by the manner in which anti-Israel protests are addressed by police and other social institutions
Simulation and reconstruction of the final momenta generated in the Coulomb explosion of iodopyridine
No full textThis entry contains data about the Coulomb explosion of 2-iodopyridine.
The simulation data contain the results of the simulation of the Coulomb explosion using the XMDYN software, under several conditions. The results contains the final momenta and charges of the ions produced in the explosion.
The reconstruction data contain the results of an algorithm that fits a Gaussian model to the final momenta of the ions in experimental condition (random molecule rotation, finite detection efficiency, unknown ion identity). The reconstruction has been applied to simulated data under several different condition and to experimental data collected at EuXFEL, at the SQS endstation.
The README.md file describe in more details the format of the other files.
The data in this entry has been used for the manuscript: "Imaging collective quantum fluctuations of the structure of a complex molecule" (in revision), and are shown in the following figures:
- Figure 2: `simulation_main.h5`, `simulation_no_GSF.h5`
- Figure 3: `reconstruction_simulation_C6_M3.h5`, `reconstruction_experimental_C6_M3.h5`
- Figure 4: `reconstruction_simulation_C6_M3.h5`, `hessian.dat`
- Figure S7: `simulation_main.h5`, `smulation_thermal_250K.h5`
- Figure S10: `simulation_main.h5`, `reconstruction_simulation_C6_M3.h5`
- Figure S11: all file `reconstruction_simulation_benchmark[..].h5`
- Figure S12: `reconstruction_simulation_C6_M3.h5`, `reconstruction_simulation_benchmark_C6_M3.h5`
- Figure S13: `reconstruction_simulation_C6_M3.h5`, `hessian.dat`
- Figure S14: `reconstruction_simulation_low_charges_C6_M3.h5`, `reconstruction_experimental_low_charges_C6_M3.h5`
- Figure S15: `reconstruction_experimental_C6_M3.h5
Antisemitismus unter Jugendlichen und Heranwachsenden in Deutschland. Aktuelle Befunde zu Entwicklungen zwischen 2022 und 2024 und Folgerungen für die Prävention. Onlinevorlesung auf Einladung des Sächsischen Institut für Polizei- und Sicherheitsforschung (SIPS) an der Hochschule der Sächsischen Polizei (FH) gehalten am 03. März 2025.
No full textProf. Dr. Peter Wetzels
(Universität Hamburg, Fakultät für Rechtswissenschaft, Institut für Kriminologie)
(Online Vorlesung für die Hochschule der Sächsischen Polizei am 3.3.2025, 18.00 – 19:30 Uhr)
Es werden Ergebnisse von zwei bundesweiten Online-Umfragen bei repräsentativen Stichproben von in Deutschland lebenden Jugendlichen und Heranwachsenden im Alter von 16 bis 21 Jahren zur Verbreitung antisemitischer Einstellungen vorgestellt. Diese Befunde der MOTRA-Studie „Jungen Menschen in Deutschland“ (JuMiD) zeigen eine sehr deutliche Zunahme klassischer Formen antisemitischer Vorurteile im Jahr 2024 im Vergleich zur ersten Befragung im Jahr 2022.
Es gibt allerdings erhebliche Unterschiede des Ausmaßes und der Entwicklungen antisemitischer Einstellungen zwischen verschiedenen Subgruppen. Diese Differenzen sind für die Bestimmung der Zielgruppen der Prävention von Antisemitismus hoch relevant. Junge Menschen mit Migrationshintergrund sind signifikant häufiger sowohl klassisch antisemitisch als auch israelfeindlich eingestellt. Die Raten für diese beiden Formen des Antisemitismus sind innerhalb der Gruppe der Migrant:innen, speziell bei jungen Musliminnen und Muslimen, besonders hoch. Der signifikante Anstieg des Antisemitismus zwischen 2022 und 2024 ist jedoch keineswegs auf die Gruppe der jungen Muslime beschränkt, sondern findet sich in allen Teilgruppen junger Menschen in Deutschland.
Die Ergebnisse multivariater Regressionsanalysen zeigen weiter, dass die hohe Prävalenz traditioneller antisemitischer Ressentiments unter jungen Muslimen weder im Jahr 2022 noch im Jahr 2024 durch ihre verstärkten Diskriminierungserfahrungen oder ihre verstärkte Wahrnehmung kollektiver Marginalisierung in der deutschen Gesellschaft erklärt werden kann. Wichtige Prädiktoren sind neben einem niedrigen Bildungsniveau der Grad der Neigung zum Verschwörungsglauben und eine rigide, fundamentalistische Auffassung von Religion.
Im Jahr 2024 finden sich sehr hohe Raten von anti-israelischer Einstellungen. Diese betreffen sowohl Kritik der Politik Israels als auch Formen eines israelbezogenen Antisemitismus. Die Prävalenzraten fallen hier erheblich höher aus als die Raten des traditionellen/klassischen Antisemitismus. Auch solche antiisraelischen Einstellungen sind bei jungen Migrant:innen, vor allem bei Jungen Muslim:innen deutlich stärker verbreitet als bei jungen Menschen ohne Migrationshintergrund.
Die Befunde, die im Grundsatz mit Erkenntnissen von Studien bei Erwachsenen übereinstimmen, sind Ausgangspunkt von Überlegungen zur Frage möglicher Konsequenzen für die Praxis der Prävention von Antisemitismus. Dabei kann auch der Polizei eine zentrale Rolle zukommen
How Assessment and Cooperation Practices Influence Suppliers' Adoption of Sustainable Supply Chain Practices: An Inter-Organizational Learning Perspective
No full textData collection via limesurvey (online survey) between December 2021 and March 2022
Sample: B2B companies in Germany, particularly from the mechanical and plant engineering (machinery), the chemical, and the electrical industrie
Beserman multimedia corpus
No full textBeserman multimedia corpus
This deposit contains transcriptions of monologues and conversations in spoken Beserman (formerly classified as a dialect of Udmurt, ISO 639-2 code udm). It contains 276 transcripts with a total of 289 thousand words (see explanations for this count below). The online version of this corpus, which is updated regularly, can be found at https://beserman.web-corpora.net/index_en.html.
Description of the contents
The contents are as follows:
eaf (directory as ZIP archive): transcripts in ELAN with clause-level translations into Russian and English, arranged by the year of recording
json (directory as ZIP archive): the same transcriptions with automatic rule-based morphological annotation, stored in tsakorpus format, arranged by the year of recording
metadata.csv: tab-delimited metadata for the transcriptions
metadata_participants.json: metadata for speakers in JSON
README.md: documentation
The associated recordings (audio or video) are stored in a separate repository (https://doi.org/10.25592/uhhfdm.17154) with a stricter access policy due to privacy concerns. You can download them separately and extract them in a directory called sound, which should be located under the same path as eaf. This way, ELAN will be able to open the media files.
Beserman language
The language spoken by the Besermans belongs to the Permic branch of Uralic languages. It is spoken by about 2000 people, who live mainly in the northwest of Udmurtia. Unfortunately, the number of speakers is rapidly decreasing, as the transmission of the language to the younger generation stopped completely between 2000 and 2005.
Beserman has traditionally been regarded as a supradialect (dialectal group, narechiye) of the Udmurt language (as well as the only dialect within this dialect). The linguistic difference between Beserman and Udmurt is small, especially if Beserman is compared to the Northern Udmurt dialects. Nevertheless, the Besermans distinguish their language from Udmurt and consider it an important factor of national identity. Beserman is de facto recognized in Udmurtia as a language different from Udmurt. The Day of Beserman language and writing is celebrated in Udmurtia on October 21. There is no official Beserman orthography at the moment. Those who write in Beserman use slightly different spellings, generally based on the Udmurt Cyrillic script. So far, two books have been published in Beserman: Vortčʼa madʼjos (by Vyacheslav Ar-Sergi and Rafail Dyukin) and Pičʼi princ (The Little Prince by Antoine de Saint-Exupéry, translated by Rafail Dyukin).
All morphological grammatical categories are expressed suffixally and agglutinatively, only indefinite and negative pronouns have prefixes. There are no traces of vowel harmony in Beserman, which is presumed to have existed in Proto-Uralic. Nominal grammatical categories include number, case and possessiveness. Verbs distinguish four morphological tenses (direct and evidential past, present and future) and index the person and number of the subject. The direct object is marked by the nominative or the accusative, depending on animateness, referential status, and other factors (differential object marking). The word order in the clause is relatively free, SOV being the default one (subject – direct object – verb).
Corpus characteristics
Language: Beserman (previously classified as a dialect of Udmurt); Russian (code-switching and some utterances by linguists)
Size: The corpus contains full transcripts of recordings, including fragments in Russian. The volume of the corpus is:
only words in Beserman by native speakers, not counting code-switching: 235 thousand words;
all words by native speakers: 256 thousand words;
total size, including utterances of Udmurt speakers, Besermans who are not native speakers, and linguists: 289 thousand words
Texts: Aligned transcripts of audio and video recordings. These were mostly recorded during field trips to the village of Shamardan (Yukamenskoye district, Udmurtia, Russia), which began in 2003. A few recordings made in several villages in the first half of the 2000s were provided by Nadezhda Lyukina.
40% of the texts (in terms of word count) are free dialogues, 35.9% are dialogs recorded during experiments on referential communication, 24% are monologues (mainly interviews in which the linguist acts as a listener, but also narratives about events or oral translations from Russian), 0.1% are songs.
94% of texts were recorded in Shamardan, the rest were recorded in Vorcha, Pyshkizh, Ozhyar, Yunda, Bagurt and Yezhgurt Pichinka.
Annotation:
Translations of sentences into Russian, including comments necessary to understand the context.
Translations of sentences into English. Translations are made with the help of automatic translator DeepL based on the Russian translation. At the moment only a small part of the translations are manually verified.
Automatic morphological annotation (lemmatization, part of speech, all inflectional categories) with uniparser_beserman_lat, 97% of word forms have at least one analysis. (Only words that do not contain digits or Latin characters are counted.) Since the analyzer is rule-based, there is ambiguity, i.e. one word form can have several different parsing options.
Partial disambiguation using Constraint Grammar rules.
Annotation of Russian loanwords.
Annotation of several lexical/semantic classes: animateness/humanness, body parts, means transport, different classes of proper names.
Annotation of the transitivity of verbs and (partially) their subcategorization frames.
Glossing.
Translations of lemmas into Russian and English.
Metadata:
title (in English and Russian)
date (at least the year) of recording
place of recording
genre and subgenre
speaker codes
codes of the linguists who participated in recording and transcribing
sex of the speaker
birth place of the speaker
birth year of the speaker
The Latin-based transcription system used in the transcripts due to a tradition established in our field trips (and enabled in the online search interface by default), is somewhat different from the standard ones. However, there is a one-to-one correspondence between characters or combinations of characters used here with the standard transcription systems.
Utterances in Russian and fragments of utterances, which the corpus authors considered code-switching, are transcribed in Russian in standard Russian orthography.
The correspondence between the transcription system used in this corpus, UPA (Uralic Phonetic Alphabet / Finno-Ugric Transcription, in the variant traditionally used in Udmurt studies), IPA (International Phonetic Alphabet) and Cyrillic-based phonetic transcription (also in the variant traditionally used in Udmurt studies) can be found in README.md.
Format
All speakers (participants) have unique ID codes. Episodic speakers whose identity is not known all get the code other. The ELAN files have three tiers per participant. Participant ID is specified as the value of the PARTICIPANT attribute and as the suffix of the tier name, following @. Tier type is specified as the prefix of the tier name, preceding @. Tier types are tx (transcription), ft_ru (free translation into Russian, including comments) and ft_en (free translation into English, including comments). For example, tx@IM is the transcription tier for the participant with the code IM. The tx tiers are time-aligned, each segment approximately corresponding to one clause or one smaller intonational unit, if there are pauses within the clause. The other two tier types are symbolically associated with the tx tier for the corresponding participant. Additionally, some files have a time-aligned tier called privacy. Segments on this tier should be beeped out in publicly accessible versions of the corpus due to privacy issues.
The file metadata.csv contains metadata for all recordings in a tab-delimited tabular format. The first line contains column headers, each of the other lines corresponds to one text (transcript). The first column contains the file name of the text without the extension.
The file metadata_participants.json contains metadata for all participants, except those that are marked as other. It contains a dictionary where the keys are IDs of the participants and the values are dictionaries with their metadata. The attribute speaker_type can equal native (native speaker of Beserman), native_udmurt (native speaker of Udmurt, but not Beserman), linguist (linguist who is not a native speaker of either Beserman or Udmurt) and russian (native speaker of Russian, but not Beserman or Udmurt, who lives in the village). The other metadata attributes and values are self-explanatory.
Annotation
Lemmatization
The lemma for nouns, relational nouns, pronouns and adjectives is the morphologically unmarked form, i.e. the non-possessive singular nominative form. The lemma for verbs is the infinitive.
Word forms containing productive derivations are lemmatized without these derivations if the corresponding lemma exists. For nouns, these are the proprietives on -o and on -em and the caritive attributivizer on -tem. For example, šʼašʼkajo 'with flower / flowers' is considered a form of the lexeme šʼašʼka 'flower' and is marked as a noun. For verbs, these are the iterative (-əl/-lʼlʼa), the detransitive (-(i)šʼk) and the productive causative (on -(ə)t, but not on -et and not in -t in verbs of the non-a conjugation), as well as the multiplicative (-ja) when it follows a causative.
Tagset
Grammatical values expressed in each word are indicated with tags. A complete list of tags used for annotating words in Beserman can be found in README.md.
Authors
Starting in 2003, the corpus texts were recorded and transcribed in the field by numerous participants of the field trips. The overwhelming majority of the corpus texts (about 80%) were recorded by Maria Usacheva (code Interviewer_MU in the transcripts) and/or Timofey Arkhangelskiy (Interviewer_TA), in some cases, together with other linguists. They, as well as Maria Berseneva, a native speaker of Beserman, prepared the vast majority of transcriptions and translations of the texts into Russian. Olga Biryuk (Interviewer_OB), Ruslan Idrisov (Interviewer_RI), Maria Cheremisinova (Interviewer_MCh), Nikolai Filippov (Interviewer_NF) and Iuliia Zubova (Interviewer_YZ) have also significantly contributed to the recording and transcription of the texts. Timofey Arkhangelskiy provides technical support for the corpus and is responsible for correcting earlier transcriptions. Sound-alignment (ELAN) of texts that were transcribed before 2015 and did not have any alignment was performed by Marina Pankova. Most of the alignment of the remaining texts with sound was done by Timofey Arkhangelskiy.
Funding
The previous publicly accessible version of the corpus (BeserCorp 1.0) was archived in the Language Bank of Finland (FIN-CLARIN): http://urn.fi/urn:nbn:fi:lb-2021052406. It was much smaller, did not have any sound alignment or English translations and had a different annotation (manual annotation in FLEX).
The preparation of this version of the corpus was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant — project no. 428175960 (Timofey Arkhangelskiy).
Contact
If you have any questions, would like to propose a collaboration, or have noticed an error in the corpus, please email Timofey Arkhangelskiy at [email protected].
References
ELAN (Version 6.9) [Computer software]. (2024). Nijmegen: Max Planck Institute for Psycholinguistics, The Language Archive. Retrieved from https://archive.mpi.nl/tla/ela
Multi-analytical data of Tibetan initiation cards from the Zhangzhung Nyengyu tsakali collection
No full textThis dataset presents the multi-analytical results of pigment analysis from six Tibetan initiation cards in the Zhangzhung Nyengyü Tsakali collection. The color palette was determined through qualitative analysis using scanning wide-angle X-ray scattering (WAXS), X-ray fluorescence (XRF), Raman spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and fiber optic reflectance spectroscopy (FORS).
According the to CSMC´s standardised system for the labelling of analytical data, all measurements are listed in an electronic lab notebook (01_Tsakali_ELN) and documented in an protocol (02_Tsakali_Protocol).
The raw and evaluated data, along with a summary file, can be found together with a summary file in the respective methods folders (XRD, XRF, Raman, FTIR, and FORS)
Support mechanisms for exiled students in Higher Education. A seven European country level synthesis
No full textIn this document, we present the support mechanisms for exiled students at HE institutions in all partner countries of the AGILE consortium, according to responses collected through an online survey. The analysis compares some of the challenges in the different countries’ HEIs and the ways they cope with them, in order to build sustainable institutional resilience when welcoming exiled students
Der Einfluss von Krieg, Klimawandel und Migration auf Autokratieakzeptanz in Deutschland. Vortrag gehalten auf der MOTRA-K 2025, Wiesbaden, 5. März 2025.
No full textThis paper investigates how global conflicts and crises influence public attitudes toward democracy in Germany, particularly fears related to war, climate change, and migration. As part of the study "People in Germany: International", online surveys are conducted every two to three months. Our data tracks how perceptions of societal challenges and associated concerns shape attitudes toward democracy over time. A new measurement is used to gauge acceptance of autocracy, defined by the rejection of democratic norms like open debate and parliamentary oversight, and support for more authoritarian leadership. Results indicate that about 30% of the German population exhibits some level of autocracy acceptance, with variations across political affiliations—from 14.8% among Green Party voters to 50.1% among AfD (a far right party) supporters. Acceptance of autocracy is not confined to right-wing or lower-educated groups but spans various social demographics. Concerns over access to necessities—housing, energy, work, and food—aggravated by fears of war, climate change, or migration, increase the likelihood of supporting autocracy. Those who view political leaders as incompetent are even more inclined toward authoritarian preferences
Teildatensatz aus der Studie Teacher Education and Development Study - Inclusive Mathematics Education (TEDS-IME) - Professionelle Unterrichtswahrnehmung, professionelles Wissen, Professionalisierungsevaluation und Deskriptiva
No full textIn dem Projekt Teacher Education and Development Study - Inclusive Mathematics Education (TEDS-IME) wurde eine innovative Professionalisierungsmaßnahme entwickelt, die für drei Zielgruppen mit unterschiedlicher Unterrichtserfahrung (Lehramtsstudierende im Master, Lehrkräfte im Vorbereitungsdienst und Lehrpersonen) implementiert wurde. Zur Messung von Professionalisierungserfolgen wurden spezifische Instrumente zur Messung von professioneller Unterrichtswahrnehmung und professionellem Wissen von Lehrkräften bzgl. inklusiver Bildung im Mathematikunterricht der Sekundarstufe entwickelt.
Der vorliegende Teildatensatz aus dem Projekt enthält die Fähigkeitsschätzer zu der professionellen Unterrichtswahrnehmung und dem professionellen Wissen der Teilnehmer*innen an der Professionalisierungsmaßnahme sowie der Personen aus der Kontrollgruppe. Des Weiteren sind Variablen zur Professionalisierungsevaluation sowie Deskriptiva inkludiert. Weitere Variablen sind nur als Leervariablen verfügbar, um die Struktur des Gesamtdatensatzes aus dem Projekt zu verdeutlichen.
Der Gesamtdatzensatz ist bei Interesse auf Nachfrage bei den Projektleitungen Prof. Dr. Johannes König ([email protected]) und Prof. Dr. Gabriele Kaiser ([email protected]) vor dem Hintergrund einer Kooperationsvereinbarung zu erhalten