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Our aim is to shed light on the impact that Eurocentric ideas and practices of dominant social groups have on mathematics education research. We suggest that the unintentional advancement of scholarly work that centers colonization and whiteness requires intentional intervention to disrupt. We identify rationales that mathematics education scholars give for not attending to equity in their work and provide actionable steps that can be taken to promote the practice of explicitly attending to issues of equity and justice in mathematics education research. We conclude with a metaphor and an invitation for our international colleagues to join us in decolonizing mathematics education research. 

Stochastic computing (SC) is a re-emerging computing paradigm providing low-cost and noise-tolerant designs for a wide range of arithmetic operations. SC circuits operate on uniform bit-streams with the value determined by the probability of observing 1’s in the bit-stream. The accuracy of SC operations highly depends on the correlation between input bit-streams. While some operations such as minimum and maximum value functions require highly correlated inputs, some other such as multiplication operation need uncorrelated or independent inputs for accurate computation. Developing low-cost and accurate correlation manipulation circuits is an important research in SC as these circuits can manage correlation between bit-streams without expensive bit-stream regeneration. This work proposes a novel in-stream correlator and decorrelator circuit that manages 1) correlation between stochastic bit-streams, and 2) distribution of 1’s in the output bit-streams. Compared to state-of-the-art solutions, our designs achieve lower hardware cost and higher accuracy. The output bit-streams enjoy a low-discrepancy distribution of bits which leads to higher quality of results. The effectiveness of the proposed circuits is shown with two case studies: SC design of sorting and median filtering