In season 4, episode 13 (chapter 52) of the hit Netflix show called House of Cards (2016), President Frank Underwood and Vice President Claire Underwood are in the situation room watching a terrorist threat come to fruition. In the live feed, the domestic terrorists are shown decapitating a hostage. Almost everyone in the room reacts with a gasp, body movement, or utterance – except Frank and Claire. This complete lack of bodily or verbal reactions demonstrates the Sensation attribute. Frank Underwood is scary sometimes.
In the hit poker movie Rounders (1998), soon-to-be dropout law school student Mike McDermott is facing a stressful poker game against Teddy KGB, a Russian mobster with his own poker club. Mike previously lost his funds to Teddy KGB and has loan sharks after him. During the final poker showdown between the two, Mike is folding good hands because he notices that Teddy KGB has him beat when he splits open and eats an Oreo cookie. This cue allowed Mike to dominate most of the hands until Teddy KGB figured it out. The outburst indicates that the Russian realized his own tell. In using phrases like "Lays down a monster. The f*** did you lay that down. Should have paid me off ...," Teddy vocalizes his own inability to use cues, logical reasoning, and predictive consideration. This is reinforced by the expletives. Teddy KGB's self-admitted mistake after speaking in a confident manner demonstrates a near-bottom example of the Inference attribute.
On June 15, 2012, South Korean K-pop artist Psy stunned the world with the release of his hit single called "Gangnam Style (강남스타일)." The viral music video features lots of action, amusing dance routines, and bright colors. The lyrics of the song discuss the culture of affluent individuals in the Gangnam region of South Korea. Moreso, Psy's lyrics describe nightlife, his behavior, attitudes towards potential romantic partners, and his affluent lifestyle. Psy's inclusion of enough details without disclosing more sensitive information demonstrates a typical example of the Specificity attribute.
In the hit movie The Wolf of Wall Street (2013), successful financer Jordan Belfort finds himself on his own boat being visited by FBI agents for financial crimes of a criminal nature. Very serious. He cordially invites them up to his boat and engages in 15 minutes of conversation warm up before the two agents and the focused-eyed Belfort begin to talk about brass tax. Belfort suggests, in so few words, that he is willing to do anything within his power to make peoples' lives better, including applying his experience and money. The FBI agent interprets this as a clear bribe, and breaks protocol by asking Jordan to repeat it again because he believes that Jordan has incriminated himself terribly. Comedic dialogue proceeds thereafter. Belfort’s knowledge of the law seemingly influenced his lack of details for how the crime would work in a logistical manner, which would constitute evidence of committing a bribery crime. Belfort's selective word choices intended to dilute clarity in order to avoid self-incrimination demonstrate communication well below average in the Specificity attribute.
An ultra low attribute score is exceptionally rare because it represents 5% of the entire population. In a room with 100 other people, a person with an ultra low attribute score would be lower than 95 of them and higher than none of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Very Low
5–10% percentile
A very low attribute score is rare because it represents 5% of the entire population. In a room with 100 other people, a person with a very low attribute score would be higher than five of them and lower than 90 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Low
10–20% percentile
A low attribute score is somewhat uncommon and represents 10% of the entire population. In a room with 100 other people, a person with a low attribute score would be higher than ten of them and lower than 80 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Slightly Low
20–40% percentile
A slightly low attribute score is common and represents 20% of the entire population. In a room with 100 other people, a person with a slightly low attribute score would be higher than 20 of them and lower than 60 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Average
40–60% percentile
An average attribute score is typical and represents 20% of the entire population. In a room with 100 other people, a person with an average attribute score would be higher than 40 of them and lower than 40 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Slightly High
60–80% percentile
A slightly high attribute score is common and represents 20% of the entire population. In a room with 100 other people, a person with a slightly high attribute score would be higher than 60 of them and lower than 20 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
High
80–90% percentile
A high attribute score is somewhat uncommon and represents 10% of the entire population. In a room with 100 other people, a person with a high attribute score would be higher than 80 of them and lower than 10 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Very High
90–95% percentile
A very high attribute score is rare because it represents 5% of the entire population. In a room with 100 other people, a person with a very high attribute score would be higher than 90 of them and lower than five of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Ultra High
95–100% percentile
An ultra high attribute score is exceptionally rare because it represents 5% of the entire population. In a room with 100 other people, a person with an ultra high attribute score would be higher than 95 of them and lower than none of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.