Warfare and European expansion in the Indian Ocean and Pacific, 1450-1850
Institutions, Guilds, and Economic Prosperity
Islam and Empire in India: The Padshah's Sacred Authority and Religious Pluralism in Mughal Times
Sanjaya Lall Fund Panel 2023: Inequality and Social Mobility in the 21st Century
Lead Speaker Professor Raj Chetty; Panellist Professor Joe Stiglitz; Panellist Anneliese Dodds MP
Discussion and Q&A followed by a reception.
Discussion and Q&A followed by a reception.
日本語の役割語における性差の表現 Expressing Gender Differences in Japanese Role Language
Abstract:
話者の性、年齢、職業・階層、出身地等と深く結び付いた話し方(発話スタイル)を役割語(role language)と呼ぶ。役割語は日本のポピュラーカルチャーで広く用いられているので、日本のマンガ・アニメや小説などの理解のためには、役割語の知識が必須である。役割語の
中でも、特に男女の性差を表す表現が発達しているので、その特徴を分析するとともに、社会言語学的な観点から問題点を指摘する。
話者の性、年齢、職業・階層、出身地等と深く結び付いた話し方(発話スタイル)を役割語(role language)と呼ぶ。役割語は日本のポピュラーカルチャーで広く用いられているので、日本のマンガ・アニメや小説などの理解のためには、役割語の知識が必須である。役割語の
中でも、特に男女の性差を表す表現が発達しているので、その特徴を分析するとともに、社会言語学的な観点から問題点を指摘する。
Sanjaya Lall Fund Lecture 2023: "Creating Equality of Opportunity: New Insights from Big Data"
PROFESSOR RAJ CHETTY
SANJAYA LALL VISITING PROFESSOR 2023
William A. Ackman Professor of Economics at Harvard University
Director of Opportunity Insights
Raj Chetty is the William A. Ackman Professor of Economics at Harvard University and the Director of Opportunity Insights, which uses big data to study the science of economic opportunity: how we can give children from all backgrounds better chances of succeeding? Chetty’s work has been widely cited in academia, media outlets, and policy discussions in the United States and beyond.
SANJAYA LALL VISITING PROFESSOR 2023
William A. Ackman Professor of Economics at Harvard University
Director of Opportunity Insights
Raj Chetty is the William A. Ackman Professor of Economics at Harvard University and the Director of Opportunity Insights, which uses big data to study the science of economic opportunity: how we can give children from all backgrounds better chances of succeeding? Chetty’s work has been widely cited in academia, media outlets, and policy discussions in the United States and beyond.
The Unfairness of Fair Machine Learning: Levelling down and strict egalitarianism by default
In recent years fairness in machine learning (ML) has emerged as a highly active area of research and development. Most define fairness in simple terms, where fairness means reducing gaps in performance or outcomes between demographic groups while preserving as much of the accuracy of the original system as possible. This oversimplification of equality through fairness measures is troubling.