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Word2vec is a popular family of algorithms for unsupervised training of dense vector representations of words on large text corpuses. The resulting vectors have been shown to capture semantic relationships among their corresponding words, and have shown promise in reducing a number of natural language processing (NLP) tasks to mathematical operations on(More)
How do firms respond to technological advances that facilitate the automation of tasks? Which tasks will they automate, and what types of worker will be replaced as a result? We present a model that distinguishes between a task's engineering complexity and its training requirements. When two tasks are equally complex, firms will automate the task that(More)
In this paper we estimate the sorting effects of university degree class on initial labor market outcomes using a regression discontinuity design that exploits institutional rules governing the award of degrees. Consistent with anecdotal evidence, we find sizeable and significant effects for Upper Second degrees and positive but smaller effects for First(More)
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