George Orwell’s 1949 dystopian novel Nineteen Eighty-Four is set in a world of perpetual war and total information control

 George Orwell’s 1949 dystopian novel Nineteen Eighty-Four is set in a world of perpetual war and total information control, where three super-states dominate the globe. The story unfolds in London, capital of the totalitarian state of Oceania. Winston Smith, a low-ranking Party member who works at the Ministry of Truth falsifying historical records, secretly doubts the Party’s absolute rule. Citizens are suppressed by round-the-clock surveillance through “telescreens” and by the Thought Police, and they are steered into hatred during the daily “Two Minutes Hate.”

The Party shackles thought by shrinking language into Newspeak and by encouraging doublethink, the simultaneous acceptance of contradictions, while its iconic leader Big Brother enforces loyalty. Winston mounts small acts of rebellion: an illicit affair with the pleasure-seeking Julia, stolen moments in a rented attic over an old bookshop, and tentative contact with the underground “Brotherhood.” Yet charismatic Inner-Party member O’Brien lays a trap, and Winston is arrested and taken to the Ministry of Love, where torture and psychological manipulation ensue.

In the final stage, Winston’s spirit collapses when his worst fear—rats—is used against him. He capitulates, internalizing the Party’s assertion that “2 + 2 = 5,” and comes to love Big Brother with total sincerity. The novel meticulously traces how freedom, truth, and personal memory can be twisted by state power, sounding an alarm that anticipates modern issues such as digital surveillance, big-data–driven opinion shaping, and fake news. Since publication, it has been a touchstone in debates on freedom of expression, resonating with incidents like the Snowden revelations and social-media manipulation scandals. “Orwellian” and “Big Brother” remain universal shorthand for critiques of the surveillance society, and the novel continues to influence film, theater, comics, and music.


Comments

Post a Comment

Popular posts from this blog

Generative Art Libraries and Resources 1. Metaball Libraries and Samples metaballs-js (npm) : A lightweight WebGL-based metaball rendering library. You can freely specify the number of balls, colors, and speed. Paper.js Metaball Demo : The official Paper.js example showing a “viscous” effect via contour calculations on the canvas. Varun.ca Metaballs : An HTML5 canvas/JavaScript demo of metaballs with the algorithm’s formulas explained. Three.js Metaball Slime : A 3D metaball example using Marching Cubes and the Rapier physics engine. Codrops “Drawing 2D Metaballs with WebGL2” : A tutorial for drawing 2D metaballs by hand in WebGL2. 2. Symmetry (Rorschach) Generative Art Symmetry Drawer by aferriss : An editor built on p5.js for drawing with left-right symmetry—perfect for experimenting with ideas. “ : A simple sample that generates patterns by pairing square cells symmetrically. Medium: From Syntax to Symmetry (p5.js) : ...
Read more

Japan Jazz Anthology Select: Jazz of the SP Era

Image
Saint Louis Blues — W.C. Handy’s iconic early jazz–blues standard, often played with a sturdy two-beat dance feel. Learn more Pagan Love Song — A Tin Pan Alley favorite by Arthur Freed & Nacio Herb Brown, frequently sweetened into a foxtrot. Learn more When It’s Lamp Lighting Time in the Valley — A sentimental waltz-time country ballad that crossed over into light-music repertoire. Learn more Chinrai-bushi — A salon-tinged popular song often adapted by prewar dance bands in Japan. Learn more Kiso-bushi — A graceful folk song from the Kiso region; arrangements highlight its lilting, modal flavor. Learn more Yagi-bushi — A lively festival min’yō from Gunma/Tochigi; its call-and-response suits a buoyant swing. Learn more Yasugi-bushi — A humorous Shimane folk song (famous for the “dojo-sukui” dance) that also works as a jaunty foxtrot. Learn more Taiko-sen (“Boat on Lake Tai”) — A Chinese popular tune widely played in Japan; often given a gentle ...
Read more

In practice, the most workable approach is to measure a composite “civility score” built from multiple indicators.

  1) Model-based indicators (machine learning) Toxicity/Aggression: Use Jigsaw’s Perspective API to obtain probabilities for “TOXICITY,” “INSULT,” “PROFANITY,” “IDENTITY_ATTACK,” etc. Japanese is supported (see the official language table). Politeness: Stanford’s research established a framework for estimating “politeness” from markers like request forms, hedges, honorifics, etc. It’s English-centric, but the methodology can be adapted to Japanese. The R package politeness is also useful. 2) Lightweight rules for Japanese (highly interpretable) Honorific/hedge rate: Ratios of “です/ます,” “〜でしょうか,” “お手数ですが,” “お願いします,” and the like. Presence of slurs/derogatory terms: A custom NG-word list (including figurative or euphemistic forms). Imperatives/strong assertions: Frequency of “〜しろ,” “〜に決まってる,” heavy use of exclamation marks, ALL-KATAKANA bursts, etc. Consideration/evidence markers: Signs of dialogic and verifiable style such as “根拠：,” “出典：,” “もし〜なら.” 3) ...
Read more