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Compliance is a central concept in both the study and practice of international relations, and the body of literature is correspondingly extensive. Although justice has already been shown to play an important role in international negotiations, its potential impact on actors’ compliance behavior has not been sufficiently explored to date. We examine the relationship between the two concepts, and posit that actors’ perceived justice considerations with a regime influence their compliance behavior. To illustrate the importance of including justice considerations in the study of compliance, we investigate Germany’s behavior as a member of the Nuclear Non-Proliferation Treaty during the 1960–80s. The empirical illustration exemplifies how a member’s justice contentions, borne of an unjust regime, can lead to contested compliance and regime conflict. The case illuminates the need to broaden our understanding of compliance and its complexity in both conceptual and practical terms.

When creating text transcripts from spoken audio, Automatic Speech Recognition (ASR) systems need to infer appropriate punctuation in order to make the transcription more readable. This task, known as punctuation restoration, is challenging since punctuation is not explicitly stated in speech. Most recent works framed punctuation restoration as a classification task and used pre-trained encoder-based transformers, such as BERT, to perform it. In this work, we present an alternative approach, framing punctuation restoration as a sequence-to-sequence task and using T5, a pretrained encoder-decoder transformer model, as the basis of our implementation. Training our model on IWSLT 2012, a common punctuation restoration benchmark, we find its performance is comparable to state of the art classification-based systems with an F1 score of 80.7 on the test set. Furthermore, we argue that our approach might be more flexible in its ability to adapt to more complex types of outputs, such as predicting more than one punctuation mark in a row.

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