You start by treating the phrase as a variable that changes over time. First, quantify the baseline: how often do you hear it in a given context, what body language accompanies it, what tone, what word choice, what previous states of the speaker? Then map each of those sub‑signals onto a vector: intonation curve, tempo, pitch range, speech rate, volume. Next, assign weights: the social cost of saying it, the speaker’s history, the emotional state of the listener. Once you have a weighted vector you can feed it into a simple logistic regression that outputs a probability of genuine affection versus performative compliance. The “odd machinery” is just a series of thresholds you’re tuning. In short, deconstruct it into measurable components, apply probability, then interpret the result in the context of the broader social contract that surrounds the phrase.