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To what extent do attitudes toward money—specifically, the love of money—moderate the relationship between public service motivation and job satisfaction among public sector professionals in China? The authors collected data from full‐time public sector professionals who also were part‐time students in a master of public administration program in eastern China. After confirmatory factor analyses, the regression results show that a public servant's love of money moderates the relationship between public service motivation and job satisfaction—that is, individuals with a strong love of money have a significantly stronger relationship between public service motivation and job satisfaction than those without, a finding that supports the "crowding‐in effect." Alternatively, for high love‐of‐money civil servants with a "steel rice bowl" mentality, high job satisfaction is explained by the best offer (output) for the minimum amount of effort (input), at least within Chinese culture. Such findings are counterintuitive in light of Chinese personal values, equity theory, public servants' institutional background, ethical organizational culture, and corruption.

AbstractMedia bias widely exists in the articles published by news media, influencing their readers' perceptions, and bringing prejudice or injustice to society. However, current analysis methods usually rely on human efforts or only focus on a specific type of bias, which cannot capture the varying magnitudes, connections, and dynamics of multiple biases, thus remaining insufficient to provide a deep insight into media bias. Inspired by the Cognitive Miser and Semantic Differential theories in psychology, and leveraging embedding techniques in the field of natural language processing, this study proposes a general media bias analysis framework that can uncover biased information in the semantic embedding space on a large scale and objectively quantify it on diverse topics. More than 8 million event records and 1.2 million news articles are collected to conduct this study. The findings indicate that media bias is highly regional and sensitive to popular events at the time, such as the Russia-Ukraine conflict. Furthermore, the results reveal some notable phenomena of media bias among multiple U.S. news outlets. While they exhibit diverse biases on different topics, some stereotypes are common, such as gender bias. This framework will be instrumental in helping people have a clearer insight into media bias and then fight against it to create a more fair and objective news environment.