#05 Categorical level normalization

Normalization Rules · Impact measurement

For ordered levels (recognition tier, digital tools tier): current level divided by the defined maximum for that variable.

Data & measurement

Normalize impact variables from heterogeneous raw measures to [0,1]. State targets v_i^target and level ceilings alongside every reported norm. Write explicit operational definitions for each symbol in your protocol, even when abbreviations look standard. Log instrument versions, sample frames, and cleaning rules whenever estimates are refreshed so longitudinal comparisons stay valid.

Solution & proof

Conceptual summary: For ordered levels (recognition tier, digital tools tier): current level divided by the defined maximum for that variable. Treat this as a measurement recipe: map each symbol to an empirical quantity, substitute estimates, and simplify with ordinary algebra (including logarithms, min/max caps, or piecewise branches where shown). Where limits or integrals appear, approximate with discrete sums on cohorts or time steps when closed forms are impractical. Interpret the result against thresholds in the cited source and report uncertainty on inputs.

Playground

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Open the playground to test sample values, review worked scenarios, and explore how this formula behaves across multiple cases.

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Source & tags

Source

Impact measurement framework — Normalization Rules

Tags

impact-measurementlevel-0-1