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Statistical Domination

The exercise of power through statistical norms and metrics. Statistical domination occurs when statistical standards (e.g., p‑values, confidence intervals, average effects) are imposed as universal benchmarks, marginalising those who cannot meet them or whose experiences are not captured by aggregate numbers. It is a form of formal domination where the statistician or data scientist holds authority over the subject, whose messy reality must be forced into statistical categories. This domination hides behind objectivity: “the numbers don’t lie” – but the numbers are always someone’s numbers.
Example: “The hospital’s patient satisfaction surveys were used to punish doctors who served complex, non‑English‑speaking populations. Statistical domination: numbers used to enforce compliance, not care.”

Data Domination

The control exerted by those who collect, store, analyse, and interpret data over those who are the subjects of that data. Data domination includes surveillance capitalism, algorithmic management, and the power to define what counts as a “data point.” It operates through asymmetry: the data‑rich dominate the data‑poor, and those who can analyse data dominate those who cannot. Data domination is reinforced by the Data Guillotine, which makes the data seem neutral while obscuring the power relations embedded in its collection and use.

Example: “Workers had no access to their own performance scores, but those scores determined their shifts. Data domination: using information as a lever of control.”
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