Leonid Sirota
10.3K posts

Leonid Sirota
@DoubleAspect
Legal academic, Associate Professor @UniRDG_Law. Mostly public law, dabble in jurisprudence; blogger, also mostly on (Canadian) public law.



I will take your non-answer as a confirmation that you did indeed take the Oath of Allegiance. I also infer that you did so in bad faith, with no intention to be faithful to and bear true allegiance to Canada’s Sovereign. And that you now advocate subverting the ancient constitutional order of the country that welcomed you. So apparently you lied in taking the oath, and are demonstrating ingratitude for the country that welcomed you. That saddens me. I understand you’re a lawyer, hence your peculiar reference to litigation. But virtues such as honesty, loyalty, and gratitude are primarily ethical, not legal principles. With respect to Bloc Québécois MPs, yes, I believe they perjure themselves when they take the Oath of Allegiance, a point I made as an MP. In my view, Sinn Féin candidates who are elected to the Westminster Parliament demonstrate how to conduct themselves ethically in an analogous situation by refusing to take the Oath, and therefore not taking their seat. Although they are in a party formerly affiliated with the Irish Republican Army, they have enough integrity not to lie when taking an oath.

Economics: The optimal level of tax evasion, govt waste, crime, and even voter fraud is often *above* zero. (Because getting to literal zero usually requires imposing dramatically higher costs & burdens on everyone else to ensure prevention of those last, few, toughest cases.)












A New York bill would ban AI from answering questions related to several licensed professions like medicine, law, dentistry, nursing, psychology, social work, engineering, and more. The companies would be liable if the chatbots give “substantive responses” in these areas.

Social scientists working with materials requiring digitization can only study what machines can read. In practice, that means printed Latin-script documents from well-funded archives. In a new working paper, I show that Vision Language Models used zero-shot outperform every existing OCR system across every script evaluated, and I propose a pipeline for deploying them on new collections. I apply it to six archival collections spanning 1.8 million pages across six countries for under $1,900.



