Decolonizing discourses teach us that we need to move away from the universalizing 'grand narratives' of knowledge production and focus on contextualizing diverse and situated experiences, epistemologies and narratives. Yet, few contributions actively demonstrate what a shift to decolonizing design means in practice. Participatory Design (PD) approaches are particularly well-suited to contributing to contemporary debates of decolonization in design due to PD's long-standing political traditions and values of equality and empowerment, but even here empirical methods and techniques to fully realize pluriversality in design are lacking. In line with the CHI 2021 theme of Making Waves. Combining Strengths, this interactive workshop will invigorate the debates and practices in HCI of decolonization by bringing together and demonstrating how designers and researchers in diverse global contexts are working with and adapting modes, concepts, methodologies and sensibilities into decolonizing design practices. Not only will this workshop provide new ways of thinking in HCI but also fuse theories and practices to develop truly transcultural approaches to HCI. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models.

In this article, we propose an analytical tool, named the Workload Profile Diagnosis (WPD) method, to evaluate the performance and quality of incident management (IM) systems in information technology (IT) service factories. Based on the normalization of ticket assignment delay and resolution time by their respective service-level agreement, the method computes and plots the spreading of ticket data on a log-log chart. By comparing the actual and desired distribution values in specific areas, the WPD method diagnoses specific problems and issues in the performance of IM systems such as resource and skill allocation and abnormal behavior, and identifies opportunities for automated resolution or assignment of tickets, increases or decreases in the resources and skills needed, and ultimately aims to strike a better balance between productivity and service quality. In addition to an in-depth description of the WPD method, this article presents its application in the diagnostics of four service pools of a large IT service factory. An empirical study conducted in the IT service factory shows that most of the problems identified by the WPD method were indeed present in the service pools, therefore providing evidence of the validity of the WPD method. We conclude discussing how managers can use the method to detect and evaluate transformational opportunities to increase productivity and service quality in a systematic manner.

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In this paper we show that corpus-level aggregation hinders considerably the capability of lexical metrics to accurately evaluate machine translation (MT) systems. With empirical experiments we demonstrate that averaging individual segment-level scores can make metrics such as BLEU and chrF correlate much stronger with human judgements and make them behave considerably more similar to neural metrics such as COMET and BLEURT. We show that this difference exists because corpus-and segment-level aggregation differs considerably owing to the classical average of ratio versus ratio of averages Mathematical problem. Moreover, as we also show, such difference affects considerably the statistical robustness of corpus-level aggregation. Considering that neural metrics currently only cover a small set of sufficientlyresourced languages, the results in this paper can help make the evaluation of MT systems for low-resource languages more trustworthy.