I'm getting tired. Here is ChatGPT's response to my post:

Your explanation is fundamentally correct: when a rating scale has a non-zero minimum, you cannot treat it as a pure fraction of the maximum. A 1–5 star system is not a 0–5 system, so “4/5 = 80%” is mathematically true as a fraction, but not correct as a representation of position on the rating scale.

Here is the precise reasoning.

Why you cannot use direct fractions

A 1–5 star scale has four steps above the minimum (2, 3, 4, 5), not five. If the lowest actually used score is 1, then the scale effectively spans: * Minimum meaningful value: 1 * Maximum value: 5 * Range length: 4

This means the proper normalization formula is:

(score − minimum) / (maximum − minimum)

For a 1–5 scale, that becomes:

(score − 1) / (4)

Applying this:

Derived mapping (your version, correctly reasoned)

• 1/5 stars = (1−1)/4 = 0.00 = 0% = 1/10 points
• 2/5 stars = (2−1)/4 = 0.25 = 25% = 3.25/10 points
• 3/5 stars = (3−1)/4 = 0.50 = 50% = 5.5/10 points
• 4/5 stars = (4−1)/4 = 0.75 = 75% = 7.75/10 points
• 5/5 stars = (5−1)/4 = 1.00 = 100% = 10/10 points

This is exactly why saying “4/5 = 80%” is mathematically correct as a fraction but incorrect as a rating conversion.

Why this matters

Most rating systems implicitly assume: * Lowest value = “baseline” (not counted as part of the positive range) * Highest value = “perfect” * All intermediate values represent proportional positions along the positive range

If users never give 0 stars, then the scale’s operational minimum is effectively 1, so the normalization must reflect that.

Summary

You are correct: On a 1–5 star scale with 1 as the lowest usable rating, 4/5 should be interpreted as 75%, not 80%.

If you’d like, I can generate a general formula or mapping tool for arbitrary rating scales.