Cockeyed.com

How much is Inside?
Pranks!
Community & Citizenship
Height Weight Chart
Science Club
Incredible Stuff
How To Guides
Travel

About
Contact

Disaster Casualties Visualization Tool: Kfar Etzion Massacre: 1948

129 Dead Men and Women

The Kfar Etzion massacre was a massacre of 129 Jews by the Arab Legion on May 13, 1948, the day before the Israeli Declaration of Independence.

This was a person. He  volunteered at a middle school, because  he  had a crush on one of the other tutors. He  was sleeping with  his  ex. This was a person. She wrote for the newspaper. This was a person. She was afraid of the water. This was a person. She had a green thumb. This was a person. He  was sort of selfish in bed. He  was a historian. This was a person. He abused cars. This was a person. He played piano. This was a person. He  had a hangover yesterday. He  was a poet. This was a person. She  was afraid of flying. This was a person. He was rebuilding an engine. This was a person. He  was afraid of flying. This was a person. He sang. This was a person. He made scrapbooks. He had lice. This was a person. She could play trumpet. This was a person. She was working  her  way through all of the shows on Netflix. This was a person. He  played soccer every weekend. This was a person. She loved Elvis. This was a person. He  was a street vendor. This was a person. He talked during movies. He could fall asleep anywhere. This was a person. She was good to people. She loved MASH. This was a person. She looked like a cartoon. This was a person. She was rebuilding an engine. This was a person. He always wore a hat. This was a person. He kept to himself mostly This was a person. He  finished reading all of the works of Homer. This was a person. He knew a lot of cops. This was a person. He was a good dancer. This was a person. He was very careful about conserving gasoline. He was rough and tumble. This was a person. She has four overdue books.  This was a person. He was kind of addicted to ebay. This was a person. She was a vegetarian. This was a person. She abused cars. This was a person. He was an awful driver. This was a person. She could juggle. This was a person. He  was afraid of flying. This was a person. She knew how to get free satelittle television. She spent a lot of time with old people. This was a person. He was an awful driver. He never carried cash. This was a person. He was a cat person. He was homophobic. This was a person. He  was a plumber. This was a person. He was polite to telemarketers. This was a person. He had just paid a crapload of money to get    teeth fixed. This was a person. He  dropped his work laptop last week, destroyed it and couldn't sleep for days. This was a person. He was gluten intolerant. This was a person. He was always in a hurry. He wore a lot of jewelry. This was a person. She  volunteered at a middle school, because  she  had a crush on one of the other tutors. This was a person. He was a trivia master. This was a person. She played a lot of social card games.  This was a person. She had bonsai trees. This was a person. She  always bought flowers for  her  desk. This was a person. She played World of Warcraft This was a person. She was an awful driver. This was a person. He had a lot of shoes. He fixed bikes. This was a person. He ate the food at convenience stores. This was a person. He picked up litter.  This was a person. He sang. This was a person. He went to the horseraces. This was a person. He had a podcast. This was a person. She was good to people. This was a person. He has a suit at the cleaners. This was a person. She was a crossword whiz. This was a person. She had a bunch of cameras. This was a person. He could play cricket. This was a person. He was left-handed. He was cockeyed. This was a person. She knew how to get free satelittle television. This was a person. She  volunteered at a middle school, because  she  had a crush on one of the other tutors. She  was a mason. This was a person. He  scalped tickets This was a person. He  was kind of an awesome lover. He  did open mike. This was a person. He  scalped tickets He talked during movies. This was a person. She overtipped. This was a person. She went to the horseraces. This was a person. He had braces on  his  teeth. This was a person. She was always in a hurry. This was a person. She was a hoarder. This was a person. He watched a lot of sports on TV, but never played them  himself. He chewed gum constantly. This was a person. He was polite to salesmen. He didn't get along with animals. This was a person. He was a skilled woodcarver. He loved oreos. This was a person. She once robbed a bank. This was a person. She smoked pot at music festivals. She loved rollerblading. This was a person. He  had VD. This was a person. She had crazy hair colors. This was a person. He could juggle. This was a person. She wore earphones all the time. This was a person. He tutored kids. This was a person. She  was sort of selfish in bed. This was a person. She had a lot of shoes. This was a person. He had braces on  his  teeth. This was a person. He loved wine. This was a person. She played a lot of social card games.  She was good to people. This was a person. He loved oreos. This was a person. He kept to himself mostly This was a person. She could fall asleep anywhere. This was a person. She got out of jail two years ago and never reunited with her family. This was a person. She survived cancer. This was a person. He could fall asleep anywhere. This was a person. He kept to himself mostly This was a person. He was very good at cleaning. He loved fine dining. This was a person. He  called in sick to work 9 times last month and was written up at work. This was a person. She went to the horseraces. This was a person. He talked during movies. He did not sleep with a pillow. This was a person. She  had been having trouble tying  her shoes because  she  pulled a muscle in her abs. She  was a virgin. This was a person. He had a bunch of tattoos. He knew a lot of cops. This was a person. He  always bought flowers for  his  desk. This was a person. She  was sort of selfish in bed. This was a person. She knew a lot of cops. This was a person. He just had the bandages removed from  plastic surgery. This was a person. She was very good at cleaning. She had extensions. This was a person. He can't watch the end of T2 without crying He knew a lot of cops. This was a person. She was gluten intolerant. She ate a lot of kale. This was a person. She had an awesome home theatre. This was a person. He knew a lot of cops. This was a person. She  loved to make out. This was a person. She was a glassblower. This was a person. She smoked pot at music festivals. This was a person. She could play banjo. This was a person. She was 4 days sober. This was a person. She was thrifty. This was a person. He loved nachos. This was a person. He  was a translator. This was a person. She always made the mashed potatoes at family get-togethers. This was a person. He loved chocolate. This was a person. She ate a lot of fish. This was a person. She ate the food at convenience stores. She has four overdue books.  This was a person. She overtipped. This was a person. She lived on breakfast bars. This was a person. She  called in sick to work 9 times last month and was written up at work. She  got a terrible haircut a few days ago and shaved  her  head to escape from it. This was a person. He was rough and tumble. This was a person. He wrote for the newspaper. He never ate breakfast. This was a person. He loved nachos. This was a person. He was afraid of the water.

View a different tragedy with the Disaster Visualization Tool

Jonestown | The Titanic | Kent State Shootings | My Lai | Lockerbie bombing | Kent State Shootings | Tiananmen Square Massacre | The Banana massacre | The Boyd Massacre | Mountain Meadows massacre | Kfar Etzion Massacre | Sharpeville Massacre | The Miami Showband Massacre | The Novocherkassk massacre | Tokyo Subway Sarin attack | Sinking of the Titanic | The Happy Land Fire | Brooklyn Bridge stampede | 1990 Pilgrim Stampede | Luxor hot air balloon crash |

Mouse-over body descriptions are randomly generated, intended to inject humanity into the raw number of dead. It cannot accurately represent the actual people who died in the tragedy.

  The Oatmeal Markup | Antiques Roadshow - The Ultimate "Neat Stuff" Show | Iphone vs. Kia | Let us Dilute that For You | Razor and Blades Business Model | Short-Circuiting the Facebook Tease Video Link | Other Websites Besides Healthcare.org which are Broken | Visualizing the Price of a Television | Personal account of working for commision at Banker's Life Insurance | The Three Problems with Child Car Seats | How Much Time is Really Left in the Basketball Game? | Who Uses Their Turn Signal? | Other Web Problems not related to Healthcare.org | The Cross-Section of a Couch | Comparing the Price of Used Car to the Price of a New Car | Rental Car Keys are Horrible | The Actual Amount of Time it Takes | Incorrect Shelf Prices at Walmart | Two Prices for Auto Body Repair | Roadside Sobriety Test | Cash in your Pennies | Get it Together Walmart | Price Increases at Fast Food Restaurants | Yard Sale is Shoe Store Scam | Disaster Casualties Visualization Tool | Walmart vs Target: 2013 | The 146 Drugs in Walmart's $4 Prescription Drug Plan | Email Concealer Codes | accumulating credit card debt | Selling a Structured Settlement | The Torn-up Credit Card Application ! Kirby Vacuum Cleaners
  • Photographic Height/Weight Chart
  • The Weight of Clothing

  • Cockeyed home page | Contact | Terms and Conditions | Updated February 27, 2013   Copyright 2013 Cockeyed.com