Mapping of Population Diversity in Canada and Germany: Different Strategies, Similar Pragmatism
Dublin Core
Title
Mapping of Population Diversity in Canada and Germany: Different Strategies, Similar Pragmatism
Description
The aim of this paper is to compare the respective approaches of Canada and Germany in statistically mapping population diversity and to offer possible explanations for the differences and commonalities observed. In order to investigate this, the paper takes into account the concept of ‘politics of belonging’ as a theoretical background and considers the functions of national statistics in categorizing different groups of people. There are different strategies of mapping population diversity and, inter alia, two models can be distinguished: while some countries explicitly include questions on elusive concepts of ‘origin’ in their population data collection, others refrain from doing so and instead derive different subgroups from information on citizenship and place of birth. Taking Canada as an example of the first group of countries and Germany of the second, and delineating recent changes within their respective strategies of measuring diversity within their populations, this paper argues that Canada and Germany converge towards a new pragmatism in the approaches of measuring diversity in population statistics.
Full text available at: https://doi.org/10.22215/rera.v11i1.255
Full text available at: https://doi.org/10.22215/rera.v11i1.255
Creator
Schultz, Caroline
Source
Canadian Journal of European and Russian Studies; 2017: RERA V11:1 Transatlantic Perspectives on Citizenship and Diversity: Changing Trends (backfile abstracts)
2562-8429
10.22215/cjers.v11i1
Publisher
Centre for European Studies, Carleton University
Date
2017-05-20
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Caroline Schultz, Mapping of Population Diversity in Canada and Germany: Different Strategies, Similar Pragmatism, Centre for European Studies, Carleton University, 2017, accessed November 8, 2024, https://igi.indrastra.com/items/show/2780