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Designing management education and development programmes for developing countries raises difficult questions concerning the role of the local culture in the content of the programmes. This issue is examined in the content of the Indonesian culture. The results of a survey of technical managers lead to recommendations and provide first‐hand commentary.

To examine whether indigenous critiques of globalization and critical theories of modernity are compatible, and how they can complement each other so as to engender more realistic theories of modern society as inherently constructive and destructive, along with practical strategies to strengthen modernity as a culturally transformative project, as opposed to the formal modernization processes that rely on and reinforce modern societies as structures of social inequality.

Comparison and assessment of the foundations, orientations, and implications of indigenous critiques of globalization and the Frankfurt School’s critical theory of modern society, for furthering our understanding of challenges facing human civilization in the twenty-first century, and for opportunities to promote social justice.

Modern societies maintain order by compelling individuals to subscribe to propositions about their own and their society’s purportedly “superior” nature, especially when compared to indigenous cultures, to override observations about the de facto logic of modern societies that are in conflict with their purported logic.

Social theorists need to make consistent efforts to critically reflect on how their own society, in terms of socio-historical circumstances as well as various types of implied biases, translates into research agendas and propositions that are highly problematic when applied to those who belong to or come from different socio-historical contexts.

An effort to engender a process of reciprocal engagement between one of the early traditions of critiquing modern societies and a more recent development originating in populations and parts of the world that historically have been the subject of both constructive and destructive modernization processes.

Diagnosing pain in neonates is difficult but critical. Although approximately thirty manual pain instruments have been developed for neonatal pain diagnosis, most are complex, multifactorial, and geared toward research. The goals of this work are twofold: 1) to develop a new video dataset for automatic neonatal pain detection called iCOPEvid (infant Classification Of Pain Expressions videos), and 2) to present a classification system that sets a challenging comparison performance on this dataset. The iCOPEvid dataset contains 234 videos of 49 neonates experiencing a set of noxious stimuli, a period of rest, and an acute pain stimulus. From these videos 20 s segments are extracted and grouped into two classes: pain (49) and nopain (185), with the nopain video segments handpicked to produce a highly challenging dataset. An ensemble of twelve global and local descriptors with a Bag-of-Features approach is utilized to improve the performance of some new descriptors based on Gaussian of Local Descriptors (GOLD). The basic classifier used in the ensembles is the Support Vector Machine, and decisions are combined by sum rule. These results are compared with standard methods, some deep learning approaches, and 185 human assessments. Our best machine learning methods are shown to outperform the human judges.