Gender, Justice and Deliberation: Women’s Voice in Post-Conflict Reconciliation
Denisa Kostovicova, Tom Paskhalis
Gender-just peace is elusive despite women’s increased participation in peace- making. Scholars have focused on the content of peace-agreements and the design of transitional justice instruments while overlooking how processes behind those outcomes may themselves be gendered. We study women’s speaking behavior to find out why women’s presence during justice-seeking does not result in gender- responsive outcomes. We apply multi-method text analysis to an original corpus of over half a million words in six languages from civil society debates in the post- conflict Balkans. These debates preceded the adoption of the Statute of the Re- gional Fact-Finding Commission that does not reflect women’s needs and concerns. Our analysis shows that male dominance at the micro-level of turn-taking and the absence of topics addressing gender-specific experience of conflict drive gender- insensitive outcome, rather than commonly assumed indicators of gender inequality such as women’s representation, including the frequency, length and the deliberative quality of their speech.
The Least Unclear Language: How Avoiding Negatives Produces Positive Understanding
Tom Paskhalis, Christian Müller
Designing valid and reliable methods for coding large quantities of text is an inherently complicated process. Manual coding of political texts can be prone to a range of problems that can lead to unreliable results. In addition to complex coding schemes, unreliability can result if the coders do not fully process the sentence when deciding on a code. If this is the case, the cognit- ive difficulty of processing sentences will influence the reliability of assigned codes. The current literature on content analysis assumes that coding errors are uncorrelated with the quantities of interest and are, to a large extent, a function of the analytical framework. However, this can produce biased estim- ated if some political actors are more likely to use certain language patterns. Psycholinguistic theory suggests that sentences with negations are inherently more difficult to process. By analyzing speeches from the US Congress and the UK House of Commons as well as party manifestos, we show that the number of negated sentences varies considerably over time and in a substant- ively meaningful way. For instance, legislators from government parties use fewer negations than their opposition counterparts. We address the question of whether linguistic features affect human misclassification rates with a re- analysis of crowd-coded party manifesto sentences and a coding experiment where we directly randomize the presence of some linguistic features. Our res- ults show whether coding errors can be tied to specific linguistic features of a coding unit and thus whether those features have the potential to bias human coding.
Work in progress
Interest Group Access to the Government: Who Gets It?
Record Linkage with Text: Matching Interest Groups in the UK
Interest Group Strategies in the Digital Era: Lobbying and Social Media