Policing on 淳于棼的賭書潑酒

不赴飯局

Fri, 19 Nov 2021 00:00:00 +0000

「加入公安隊伍，就要準備好站著進來、躺著出去。什麼是躺著出去？就是時刻準備著，為黨為人民犧牲一切。」

這是時代楷模、福建省公安廳黨委原委員、福州市原副市長、公安局原局長潘東昇始終奉為圭臬的一句話。

9 月 25 日，潘東昇因長期超負荷工作，積勞成疾，在重要會議安保維穩工作崗位上突發疾病，經全力搶救無效，不幸因公犧牲，年僅 57 歲。

他帶領福州公安先後打掉涉黑組織 35 個、惡勢力犯罪集團 169 個，福州市公安局因此榮獲“全國掃黑除惡專項鬥爭先進集體”。他以警心踐行初心，以生命詮釋使命。37 年來，忠誠履職、甘於奉獻，先後榮立個人二等功 2 次、三等功 1 次，榮獲全國掃黑除惡專項鬥爭先進工作者，將畢生精力和全部心血都獻給了崇高的人民公安事業。

潘東昇畢業於計算機軟件專業，是一個“技術尖兵”。他大刀闊斧推進“互聯網+”便民服務，推動公安數據共享，讓群眾辦護照等證件從 7 天變為立等就取；他推動研發警用地理信息系統、公安交通大數據平台，讓民警最快一分鐘內就能到場處置。

他是不赴飯局的公安局長。他說：

「如果有人約我吃飯，我覺得很難受，覺得很厭惡。如果大家哪一天，哪一民警，你看到我在哪個飯局上，你過來甩我兩個耳光。」

參考在這裏、這裏和這裏。

Never Run When You are Right

Sat, 09 May 2020 00:00:00 +0000

Prologue

On September 11, 1959, Frank Serpico joined the New York City Police Department as a probationary patrol man.

On 3 February 1971, he pretended to make a drug purchase and attempted to make drug dealers to open the door. A suspect opened the door a few inches. He wedged his body in. He asked his colleagues to help. They ignored him. The suspect shot him in the face with a .22 LR pistol. The bullet struck just below his eye, lodging at the top of his jaw. He began to bleed profusely. He fired back striking his assailant to the floor.

Policing - adapting to protest

Wed, 26 Jun 2019 00:00:00 +0000

Why study history?

The answer is because we virtually must, to gain access to the laboratory of human experience. When we study it reasonably well, and so acquire some usable habits of mind, as well as some basic data about the forces that affect our own lives, we emerge with relevant skills and an enhanced capacity for informed citizenship, critical thinking, and simple awareness. – Peter N. Stearns, Why Study History? (1998)

Ch 1 Big Data's watch eye

Mon, 28 May 2018 00:00:00 +0000

Big data’s watchful eye
- What is big data?
- Examples

Big data’s watchful eye

“The world is full of obvious things which nobody by any chance ever observes.”

— Sir Arthur Conan Doyle. Sherlock Holmes: the Hound of the Baskerville, 28 (ebook pub. 2016)

What is big data?

Report to the President

“There are many definitions of big data which may differ depending on whether you are a computer scientist, a financial analyst, or an entrepreneur pitching an idea to a venture capitalist. Most definitions reflect the growing technological ability to capture, aggregate, and process an ever-greater volume, velocity and variety of data.”