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Comparative scholars of legislative politics continue to face the challenge of measuring a key theoretical concept: conflict at the level of legislative bills. We address this challenge with a multilingual sentiment‐based approach and show that such a measure can effectively capture different types of parliamentary conflict. We also demonstrate that an automated translation of the dictionary yields valid results and therefore greatly facilitates comparative work on legislatures. Our applications show that a sentiment approach recovers government‐opposition dynamics in various settings. The use of a simple, translatable sentiment dictionary opens up the possibility of studying legislative conflict in bill debates across languages and countries.

AbstractDo increasing, and increasingly diverse, immigration flows lead to declining support for redistributive policy? This concern is pervasive in the literatures on immigration, multiculturalism and redistribution, and in public debate as well. The literature is nevertheless unable to disentangle the degree to which welfare chauvinism is related to (a) immigrant status or (b) ethnic difference. This paper reports on results from a web-based experiment designed to shed light on this issue. Representative samples from the United States, Quebec, and the “Rest-of-Canada” responded to a vignette in which a hypothetical social assistance recipient was presented as some combination of immigrant or not, and Caucasian or not. Results from the randomized manipulation suggest that while ethnic difference matters to welfare attitudes, in these countries it is immigrant status that matters most. These findings are discussed in light of the politics of diversity and recognition, and the capacity of national policies to address inequalities.

Is international migration a threat to the redistributive programmes of destination countries? Existing work is divided. This paper examines the manner and extent to which increases in immigration are related to welfare state retrenchment, drawing on data from 1970 to 2007. The paper makes three contributions: (1) it explores the impact of changes in immigration on social welfare policy over both the short and medium term; (2) it examines the possibility that immigration matters for spending not just directly, but indirectly, through changes in demographics and/or the labour force; and (3) by disaggregating data on social expenditure into subdomains (including unemployment, pensions, and the like), it tests the impact of immigration on different elements of the welfare state. Results suggest that increased immigration is indeed associated with smaller increases in spending. The major pathway is through impact on female labour force participation. The policy domains most affected are ones subject to moral hazard, or at least to rhetoric about moral hazard.

The article focuses on a research program concerning diversity and cautiously highlights the optimism on the incapacity of growing diversity in reducing Canada's social solidarity. It mentions the development of a welfare state that aims to protect citizens from securities and risks underlying the market economy. It also explains the adoption of a more expansive immigration programs and policies that have a greater recognition to difference through Aboriginal rights and multiculturalism.

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This study examines the level of politicization and polarization in COVID-19 news in U.S. newspapers and televised network news from March to May 2020. Using multiple computer-assisted content analytic approaches, we find that newspaper coverage is highly politicized, network news coverage somewhat less so, and both newspaper and network news coverage are highly polarized. We find that politicians appear in newspaper coverage more frequently than scientists, whereas politicians and scientists are more equally featured in network news. We suggest that the high degree of politicization and polarization in initial COVID-19 coverage may have contributed to polarization in U.S. COVID-19 attitudes., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2020.)