TY  - JOUR
A1  - Fritsch, Nina-Sophie
A1  - Verwiebe, Roland
A1  - Liedl, Bernd
T1  - Declining Gender Differences in Low-Wage Employment in Germany, Austria and Switzerland
JF  - Comparative Sociology
N2  - Although the low-wage employment sector has enlarged over the past 20 years in the context of pronounced flexibility in restructured labor markets, gender differences in low-wage employment have declined in Germany, Austria and Switzerland. In this article, the authors examine reasons for declining gender inequalities, and most notably concentrate on explanations for the closing gender gap in low-wage employment risks. In addition, they identify differences and similarities among the German-speaking countries. Based on regression techniques and decomposition analyses (1996-2016), the authors find significantly decreasing labor market risks for the female workforce. Detailed analysis reveals that (1) the concrete positioning in the labor market shows greater importance in explaining declining gender differences compared to personal characteristics. (2) The changed composition of the labor markets has prevented the low-wage sector from increasing even more in general and works in favor of the female workforce and their low-wage employment risks in particular.
KW  - low-wage employment
KW  - gender inequality
KW  - labor market
KW  - Germany
KW  - Austria
KW  - Switzerland
Y1  - 2019
U6  - https://doi.org/10.1163/15691330-12341507
SN  - 1569-1322
SN  - 1569-1330
VL  - 18
IS  - 4
SP  - 449
EP  - 488
PB  - Brill
CY  - Leiden
ER  - 
TY  - JOUR
A1  - Verwiebe, Roland
T1  - Werte und Wertebildung - einleitende Bemerkungen und empirischer Kontext
JF  - Werte und Wertebildung aus interdisziplinärer Perspektive
Y1  - 2019
SN  - 978-3-658-21975-8
SP  - 1
EP  - 22
PB  - Springer
CY  - Wiesbaden
ER  - 
TY  - JOUR
A1  - Verwiebe, Roland
A1  - Wolf, Margarita
A1  - Seewann, Lena
T1  - Werte, Wertebildung und ihre interdisziplinäre Deutung
JF  - Werte und Wertebildung aus interdisziplinärer Perspektive
Y1  - 2019
SN  - 978-3-658-21975-8
SP  - 285
EP  - 307
PB  - Springer
CY  - Wiesbaden
ER  - 
TY  - JOUR
A1  - Verwiebe, Roland
A1  - Seewann, Lena
T1  - Werte und Wertebildung in der Einwanderungsgesellschaft
JF  - Werte und Wertebildung aus interdisziplinärer Perspektive
Y1  - 2019
SN  - 978-3-658-21975-8
SP  - 239
EP  - 264
PB  - Springer
CY  - Wiesbaden
ER  - 
TY  - JOUR
A1  - Kazepov, Yuri
A1  - Verwiebe, Roland
T1  - Is Vienna still a just city?
BT  - the challenges of transitions
JF  - Vienna
Y1  - 2022
SN  - 978-0-367-68011-4
SN  - 978-1-003-13382-7
SN  - 978-0-367-68013-8
U6  - https://doi.org/10.4324/9781003133827-1
SP  - 1
EP  - 14
PB  - Routledge
CY  - London
ER  - 
TY  - JOUR
A1  - Riederer, Bernhard Edwin
A1  - Verwiebe, Roland
A1  - Ahn, Byeongsun
T1  - Professionalisation, polarisation or both?
BT  - economic restructuring and new divisions of labour
JF  - Vienna
Y1  - 2022
SN  - 978-0-367-68011-4
SN  - 978-1-003-13382-7
SN  - 978-0-367-68013-8
U6  - https://doi.org/10.4324/9781003133827-10
SP  - 99
EP  - 114
PB  - Routledge
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Seewann, Lena
A1  - Verwiebe, Roland
A1  - Buder, Claudia
A1  - Fritsch, Nina-Sophie
T1  - “Broadcast your gender.”
BT  - A comparison of four text-based classification methods of German YouTube channels
JF  - Frontiers in Big Data
N2  - Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
KW  - text based classification methods
KW  - gender
KW  - YouTube
KW  - machine learning
KW  - authorship attribution
Y1  - 2022
U6  - https://doi.org/10.3389/fdata.2022.908636
SN  - 2624-909X
IS  - 5
PB  - Frontiers
CY  - Lausanne, Schweiz
ER  -