clutterScore, scamness, unauthoritativeScore: Three Quality Demotions
The three signals that penalize layout overload, fraud proximity, and untrustworthiness — and why they combine into a single Trust signal
Three demotions in one system
System 15 combines three distinct quality demotions: clutterScore measures layout overload — too many ads, pop-ups, and distracting elements that disrupt the information flow. scamness measures fraud proximity — patterns that resemble known scams or deceptive practices. unauthoritativeScore flags content that lacks the E-E-A-T signals expected for its topic category.
Each demotion operates independently but feeds into the same Trust signal (T: primary). A page can trigger one, two, or all three demotions. The combined effect is multiplicative, not additive: a page with high clutter AND high scamness AND low authority receives a much heavier penalty than the sum of individual penalties.
The three signals represent different aspects of trust violation. Clutter violates the user's attention — a page that buries content under ads is not trustworthy. Scamness violates the user's safety — a page that resembles known scams is dangerous. Unauthoritativeness violates the user's expectations — a page that claims expertise without demonstrating it is misleading.
clutterScore: layout overload
clutterScore measures how much the layout interferes with content consumption. A page with one banner ad and clean text has a low clutter score. A page with five ads, two pop-ups, a sticky header, and interstitials has a high clutter score — the content is there, but the user has to fight through clutter to find it.
The Google API leak confirmed the existence of a clutterScore field. The field directly measures layout quality — not content quality. A page can have excellent content and still receive a high clutterScore if the layout is overloaded with ads and distractions.
clutterScore also has an indirect Authority signal (A: indirect). This makes sense: a cluttered page signals a publisher that prioritizes ad revenue over user experience, which undermines authority. A clean, focused page signals a publisher that values the reader's attention.
scamness: fraud proximity
scamness measures how closely a page resembles known scam patterns. This is not about whether the page IS a scam — it is about whether the page shares characteristics with pages that have been identified as scams. A page that uses high-pressure sales tactics, fake countdown timers, or misleading testimonials will have a high scamness score even if the product is legitimate.
The scamness signal is particularly important for YMYL (Your Money Your Life) pages. Financial advice pages, medical information pages, and e-commerce pages face higher scamness scrutiny because the potential harm from scams in these categories is greater.
scamness is also fed by contentEffort (System 9) — the effort signal. A page that required significant editorial effort is less likely to be a scam. Scammers typically produce low-effort content: copy-paste templates, generated text, and recycled images. The connection between scamness and contentEffort creates a two-signal defense: effort and pattern recognition.
unauthoritativeScore: E-E-A-T deficit
unauthoritativeScore flags content that lacks the E-E-A-T signals expected for its topic. A medical article without author credentials, a financial page without disclaimer, or a legal guide without attorney attribution will receive a high unauthoritativeScore — the content may be accurate, but it doesn't demonstrate authority.
This is the connection to IS-Calibration (System 12). Raters are trained to evaluate E-E-A-T: does the page demonstrate expertise, authoritativeness, and trustworthiness? unauthoritativeScore learns to predict what a rater would say — and if the rater would say 'this page doesn't demonstrate authority,' the model assigns a high score.
The key distinction: unauthoritativeScore is not about whether the content is wrong. It is about whether the content demonstrates the E-E-A-T signals that Google's raters look for. A factually correct page without author attribution may still receive a high unauthoritativeScore because it doesn't signal expertise.
Implications for SEO practitioners
The three demotions create a comprehensive quality floor. A page must pass all three checks: not cluttered, not scammy, and authoritative. Failing any one demotion is recoverable — failing all three is a strong negative signal.
For ad-heavy sites, clutterScore is the primary risk. The solution is not to remove all ads — it is to ensure that ads don't interfere with content consumption. Interstitials that can be dismissed, ads that are clearly separated from content, and a clean mobile layout all reduce clutterScore.
For YMYL content, unauthoritativeScore is the primary risk. The solution is to add E-E-A-T signals: author bylines with credentials, editorial policies, fact-checking notes, and expert review badges. These are not decorative — they are signals that the quality model evaluates.
For any content, scamness is a risk if the page uses patterns associated with scams. High-pressure language, fake urgency ('Only 3 left!'), and testimonials that look manufactured all increase scamness. Removing these patterns is both good UX and good SEO.