Martijn Schoonvelde

In contemporary European Union (EU) politics, the alignment of EU policies with citizen preferences has become a topic of intensive debate, especially as European integration has shifted from a ‘pe...

How do issue‐owning parties adapt their rhetoric when transitioning from opposition to government? Focusing on the Green parties in Germany and Ireland, we analyze legislative debates to trace how these parties seek to maintain ownership of environmental issues. Using more than 1.7 million parliamentary speeches from the German Bundestag (1991–2018) and the Irish Dáil (1992–2013), we apply a fictitious prediction problem approach implemented as a multiclass text‐classification task to measure distinctiveness in parties' legislative speeches. Our findings show that both parties increased their rhetorical distinctiveness on environmental issues during their first time in government, but with key differences: the Irish Greens maintained a distinct profile throughout their term, while the German Greens' distinctiveness increased as elections neared. No such patterns emerge for welfare, a non‐owned issue. Our study offers a framework and a transferable method for studying how smaller parties navigate between coalition influence and visibility through the issues they own.

This study investigates researcher variability in computational reproduction, an activity for which it is least expected. Eighty-five independent teams attempted numerical replication of results from an original study of policy preferences and immigration. Reproduction teams were randomly grouped into a ‘transparent group’ receiving original study and code or ‘opaque group’ receiving only a method and results description and no code. The transparent group mostly verified original results (95.7% same sign and p -value cutoff), while the opaque group had less success (89.3%). Second-decimal place exact numerical reproductions were less common (76.9 and 48.1%). Qualitative investigation of the workflows revealed many causes of error, including mistakes and procedural variations. When curating mistakes, we still find that only the transparent group was reliably successful. Our findings imply a need for transparency, but also more. Institutional checks and less subjective difficulty for researchers ‘doing reproduction’ would help, implying a need for better training. We also urge increased awareness of complexity in the research process and in ‘push button’ replications.

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

We identify three gaps that limit the utility and obstruct the progress of computational text analysis methods (CTAM) for social science research. First, we contend that CTAM development has prioritized technological over validity concerns, giving limited attention to the operationalization of social scientific measurements. Second, we identify a mismatch between CTAMs’ focus on extracting specific contents and document-level patterns, and social science researchers’ need for measuring multiple, often complex contents in the text. Third, we argue that the dominance of English language tools depresses comparative research and inclusivity toward scholarly communities examining languages other than English. We substantiate our claims by drawing upon a broad review of methodological work in the computational social sciences, as well as an inventory of leading research publications using quantitative textual analysis. Subsequently, we discuss implications of these three gaps for social scientists’ uneven uptake of CTAM, as well as the field of computational social science text research as a whole. Finally, we propose a research agenda intended to bridge the identified gaps and improve the validity, utility, and inclusiveness of CTAM.

The European Union's Economic Partnership Agreements (EPAs) with countries in the African, Caribbean and Pacific (ACP) group are touted as a new form of equitable engagement. However, many argue that the EPAs simply substitute a different form of political and economic domination. In this paper, we consider if the siting of meetings has a substantive impact on EPA outcomes or media reporting thereof. Using a difference‐in‐difference like approach we evaluate if the tone and polarity of media reports about the EPAs during periods of ‘home’ meetings in the ACP countries differs from media reports during ‘away’ meetings in the EU. Using two different datasets we arrive at differing results, leading to inconclusive overall findings. While we suspect that the alternating meeting site norm has implications for EPA process and outcomes, further research will be needed to uncover the precise nature of these effects.