Content Moderation Labeling

Content moderation labeling assigns real user- or model-generated content into policy categories (harassment, spam, hate speech, misinformation, self-harm, and so on) along with a severity or action tier, such as allow, flag, or remove. It's the annotation work that powers both live moderation systems and the safety policy enforcement datasets used to train and evaluate model refusals.

This work differs from narrower tasks like toxicity annotation in that it typically spans many policy categories at once rather than one axis, and it usually requires labelers to weigh context — intent, audience, and platform norms — rather than pattern-match on keywords.

Because moderation labeling involves repeated exposure to harmful content, reputable platforms build in rotation limits, support resources, and clear escalation paths for annotators doing this work.