Soft-output detection of the golden code is an important but computationally difficult task. We propose a low-and fixed-complexity soft-output detector for the golden code that uses linear equalization to simplify the task of finding a list of candidate values for one pair of information symbols, and then - for each pair on the list - it uses decision-feedback equalization to find candidate values for the remaining pair of information symbols. We propose a simple ordering algorithm that exploits the golden code's structure to ensure that the overall algorithm performs well. Numerical results indicate that the proposed algorithm is significantly less complex than previously reported algorithms, yet performs comparably.