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 the question of how processes that lead to those outcomes may themselves be gendered. We study women’s speaking behavior to find out why women’s representation in justice-seeking does not result in gender-responsive outcomes. We apply multi-method quantitative text analysis to an original corpus of over half a million words in six languages from civil society debates about reconciliation in the post-conflict Balkans. Our analysis shows that male dominance at the micro-level of turn-taking and the absence of topics addressing gender-specific experience of conflict lead to gender-insensitive outcomes, rather than commonly assumed indicators of gender inequality such as women’s representation, including the frequency, length and the deliberative quality of their speech. This study also contributes to understanding women’s role and influence in political debates.
Data in Transitional Justice: Technological Advances, Theoretical Gains and Ethical Dilemmas
Denisa Kostovicova, Rachel Kerr, Ivor Sokolic, Tiffany Fairey, Henry Redwood, Jelena Subotic, Tom Paskhalis
New digital technologies have transformed the landscape of transitional justice research. The ‘digital turn’ has led to an explosion in the amount and types of data created through social media channels, data digitisation has made existing data more easily accessible, and raised new questions around its curation, while new technologies have made possible innovative analytical techniques. These developments, and their theoretical and ethical implications are as yet poorly understood. We draw on new research using digital archives, court transcripts, social media (Facebook) and visual images. We show how, in each of these domains, new digital technologies have enabled us to: expand empirical evidence for scholarly claims; to understand the mechanics of transitional justice processes by analysing how data is produced and curated; and to shift the focus from normative rhetorical claims about transitional justice goals on to how transitional justice is enacted and articulated as particular social and political processes.
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