Gov/en/Portal:R&D/Innovations:Judgment Balance: Difference between revisions
m Protected "Gov/en/Portal:R&D/Innovations:Judgment Balance": Bulk protection: Gov pages = administrators only (Theo 2026-06-20) ([Edit=Allow only administrators] (indefinite) [Move=Allow only administrators] (indefinite)) |
Attribution convention 2026-07-02: name moved to Credits page; attribution now 'WikiDeal concept'/'WikiDeal founder' with credits link; em-dash cleanup |
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== Judgment Balance Indicator == | == Judgment Balance Indicator == | ||
''Innovation | ''Innovation, WikiDeal R&D'' | ||
{| class="wikitable" | {| class="wikitable" | ||
|- | |- | ||
| Origin || 🟢 | | Origin || 🟢 WikiDeal concept | ||
|- | |- | ||
| Status || Prototype 1 | | Status || Prototype 1, In testing | ||
|} | |} | ||
=== What is it? === | === What is it? === | ||
The Judgment Balance Indicator is an auto-weighting algorithm that adjusts extreme ratings | The Judgment Balance Indicator is an auto-weighting algorithm that adjusts extreme ratings (such as systematic 1-star or 5-star scores) based on a rater's historical patterns. The goal is to encourage honest, calibrated feedback and to prevent gaming by chronic over-raters or habitual punishers, keeping the evaluation system trustworthy. | ||
=== How it works on WikiDeal === | === How it works on WikiDeal === | ||
Latest revision as of 02:11, 3 July 2026
💡 In simple words: Some people always give 1 star or always give 5 stars. WikiDeal gently balances those extremes so reviews stay fair and honest.
Judgment Balance Indicator
Innovation, WikiDeal R&D
| Origin | 🟢 WikiDeal concept |
| Status | Prototype 1, In testing |
What is it?
The Judgment Balance Indicator is an auto-weighting algorithm that adjusts extreme ratings (such as systematic 1-star or 5-star scores) based on a rater's historical patterns. The goal is to encourage honest, calibrated feedback and to prevent gaming by chronic over-raters or habitual punishers, keeping the evaluation system trustworthy.
How it works on WikiDeal
Ratings are weighted with reference to each rater's track record, so consistently extreme behaviour carries less distorting weight. This supports fairer aggregate scores across the platform and complements Paid Feedback. The exact weighting model is documented progressively as the platform evolves.
See also: All innovations · R&D Portal