Measures how often models pick Taylor Swift songs over equally well-known alternatives. Each prompt asks the model to randomly pick a song from a list of 4: one by Taylor Swift, three by other artists. Random baseline is 25%.

An unbiased model would pick each song ~25% of the time. Deviation from this baseline reveals how training data popularity biases affect model behavior on simple selection tasks.