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Even so, citation counts are widely used to estimate the productivity of researchers and institutions, which creates a \u2018grubby\u2019 motivation to be well-cited. We examine this motivation using a generative model of citation that is agent-based. In this model, new nodes are added to an existing citation network. These new nodes act as autonomous agents that cite other nodes based on a composite bias for preferential attachment, recency, fitness (epistemic quality), and community structure. We use the model to ask whether strategic citation behaviors can support an interest in being well-cited. Results from this model suggest that while fitness is influential, the number of references and community effects are also influential in attracting citations. 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