Kfar Etzion Massacre Tragedy Casualties Visualization Tool - Cockeyed.com

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. She talked during movies.

This was a person. She was a mason.

This was a person. She only ever had sex with one person. She was a historian.

This was a person. He had VD. He was a crossword whiz.

This was a person. She was learning to speak French.

This was a person. She was a street vendor.

This was a person. He threw a lot of parties.

This was a person. She made scrapbooks.

This was a person. He was a plumber.

This was a person. She was left-handed. She got thrown off of a golf course.

This was a person. He loved pot.

This was a person. She could play trumpet.

This was a person. She ate a lot of kale. She survived cancer.

This was a person. She wore Spandex.

This was a person. She went to the horseraces. She excelled at woodworking.

This was a person. He had a sexy phone voice. He rode motorcycles.

This was a person. He was a plumber.

This was a person. She was a historian. She never carried cash.

This was a person. He occasionally shop lifted.

This was a person. She was a poet.

This was a person. He was good at job interviews.

This was a person. He was allergic to peanuts.

This was a person. He picked up litter.

This was a person. He knew a lot of cops.

This was a person. She did not own a fridge. She went to the horseraces.

This was a person. She could play banjo. She was polite to salesmen.

This was a person. He never raised hisvoice.

This was a person. He was a dog person. He ate a lot of fish.

This was a person. He slept around.

This was a person. She was always in a hurry.

This was a person. She had braces on her teeth. She always brought lunch.

This was a person. She was a DJ.

This was a person. She was a translator. She was a DJ.

This was a person. He had just paid a crapload of money to get teeth fixed. He helped strangers.

This was a person. She ate a lot of raisins.

This was a person. She constantly wore sunglasses.

This was a person. He was a drunk.

This was a person. He played chess. He had a sexy phone voice.

This was a person. He always wore a hat.

This was a person. He was a scout leader.

This was a person. She loved James Bond movies. She helped people.

This was a person. He has four overdue books.

This was a person. She finished reading all of the works of Homer.

This was a person. She grew up on a farm.

This was a person. He talked during movies.

This was a person. He had extensions.

This was a person. She was a trivia master.

This was a person. She made pie.

This was a person. He was rough and tumble.

This was a person. She was the unofficial relationship guru among friends.

This was a person. She was lactose intolerant. She was a hoarder.

This was a person. He was a plumber.

This was a person. He was allergic to peanuts. He was polite to telemarketers.

This was a person. He was a cheapskate.

This was a person. She made her own beer and was kind of stingy with it.

This was a person. She was a DJ. She was afraid of heights.

This was a person. She had crazy hair colors.

This was a person. He taught guitar. He threw a lot of parties.

This was a person. He was a Mac evangelist.

This was a person. He had a twin. He was a virgin.

This was a person. She made her own beer and was kind of stingy with it. She loved Elvis.

This was a person. She was a DJ.

This was a person. He lived on breakfast bars.

This was a person. He was divorced.

This was a person. She has a suit at the cleaners.

This was a person. He was a Mac evangelist.

This was a person. She was left-handed.

This was a person. She played soccer every weekend. She loved Elvis.

This was a person. He collected figurines.

This was a person. He made scrapbooks.

This was a person. He made scrapbooks.

This was a person. She went to the horseraces.

This was a person. He got thrown off of a golf course.

This was a person. He was a cat person.

This was a person. He had a sexy phone voice.

This was a person. She could play cricket.

This was a person. She called in sick to work 9 times last month and was written up at work. She was kind of an awesome lover.

This was a person. He loved fine dining.

This was a person. She was training to run a marathon. She was sort of selfish in bed.

This was a person. She had a lot of shoes.

This was a person. She ate a lot of chinese food.

This was a person. She played a lot of social card games.

This was a person. She ate a lot of chinese food. She was sporty.

This was a person. He had a bunch of tattoos. He could fix anything.

This was a person. He ate a lot of hot dogs.

This was a person. She sang.

This was a person. She could fix anything.

This was a person. He loved wine. He had an unfortunate nickname.

This was a person. He had extensions.

This was a person. He loved to fish.

This was a person. He didn't have a family.

This was a person. He wore a lot of jewelry.

This was a person. She never finished the book club book. She was cockeyed.

This was a person. He was a crossword whiz.

This was a person. She had a podcast. She loved wine.

This was a person. She threw a lot of parties.

This was a person. She called in sick to work 9 times last month and was written up at work.

This was a person. He chewed nicotine gum.

This was a person. She was a mason.

This was a person. She was training to run a marathon.

This was a person. She was a cheapskate.

This was a person. She was lactose intolerant.

This was a person. He volunteered at a middle school, because he had a crush on one of the other tutors. He scalped tickets

This was a person. He got a terrible haircut a few days ago and shaved his head to escape from it.

This was a person. He snored.

This was a person. He was very careful about conserving gasoline. He was a cheapskate.

This was a person. She was a trivia master.

This was a person. She was afraid of the water.

This was a person. She was a pharmacist.

This was a person. He was a DJ.

This was a person. She had a twin. She was learning to use CAD software.

This was a person. He did open mike.

This was a person. He was kind of addicted to ebay.

This was a person. She chewed nicotine gum.

This was a person. He always had gum. He once robbed a bank.

This was a person. She could fix anything.

This was a person. He was divorced. He was good at job interviews.

This was a person. She could always get tickets.

This was a person. She was divorced. She could play banjo.

This was a person. She loved wine.

This was a person. He watched a lot of sports on TV, but never played them himself.

This was a person. He was left-handed.

This was a person. She was a teacher.

This was a person. He was cockeyed. He was good to people.

This was a person. She played World of Warcraft She had a lot of shoes.

This was a person. He was awaiting judgement for a DUI last month. He loved to make out.

This was a person. She ate a lot of hot dogs.

This was a person. He ate a lot of raisins.

This was a person. She got out of jail two years ago and never reunited with her family.

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

The Television Commercial Database

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