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Monster: The Ed Gein Story - a Chilling Tale of Depravity, Mental Illness and Loneliness
The Netflix series dramatizes Ed Gein’s 1940s-50s crimes and explores his lasting influence on American horror, with only two confirmed murders and extensive grave robbing.
- On Oct. 3, Netflix released Monster: The Ed Gein Story, the third Monster anthology installment starring Charlie Hunnam and created by Ryan Murphy and Ian Brennan.
- Augusta Gein's domineering religion shaped Ed Gein's isolation, and he confessed to exhuming nine female graves and making artifacts influenced by Ilse Koch.
- The show invents several murders and romantic subplots, including Evelyn Hartley and hunters Victor Travis and Raymond Burgess, though only Mary Hogan and Bernice Worden are confirmed victims.
- Authorities arrested Ed Gein in 1957, and medical experts later found him legally insane, leading to his lifelong institutionalization at Mendota Mental Health Institute and Central State Hospital.
- The series holds a mirror to true-crime fandom, using Gein's story to reflect on America's obsession, but critics called this Monster anthology entry morally dubious while Charlie Hunnam, actor's voice divided true-crime audiences.
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These 6 Details In Netflix’s ‘Monster: The Ed Gein Story’ Were Made Up And Didn’t Really Happen
The so-called Butcher of Plainfield, Ed Gein, comes to life in Ryan Murphy’s Netflix contribution, where Charlie Hunnam becomes part of a grim picture to induce horror—but not everything in the series is true. Gein was born in the early 1900s and was thought of as a quiet Wisconsin farmer as an adult, until he was arrested in 1957 for the shooting of local hardware owner Bernice Worden. While he would later admit to taking another woman’s life, …
·Boston, United States
Read Full ArticleFor the third season of the Netflix series "Monster", Ryan Murphy wanted to tell the true story of Ed Gein but allowed some script freedoms.
·Paris, France
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Total News Sources19
Leaning Left7Leaning Right0Center1Last UpdatedBias Distribution88% Left
Bias Distribution
- 88% of the sources lean Left
88% Left
L 88%
12%
Factuality
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