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Liberationist Ethics and the Origin of Self-Regard
No full textThis is the inaugural work of liberationist ethics, which is a living dialogue with contemporary religious, philosophical, and cultural discourses and their interlocutors. I provoke questions of selfhood, vitality, and misery in the human condition and in religion. In particular, this work explores the origin of self-regard and how I (the very consciousness of ourselves) emerges as both a personal subject (bound as a social creature) and a universal subject (bound as a spiritual mode of being).
Liberationist ethics approach consciousness (or I), the individual person (oneself), community (you), and God (the greater) with deep concern for ethical relationship, irreducible subjective personhood, and dignified human flourishing.Author's Origina
A New Algorithm to Efficiently Match U.S. Census Records and Balance Representativity with Match Quality
No full textWe introduce a record linkage algorithm that allows one to (1) efficiently match hundreds of millions of records based not just on demographic characteristics but also name similarity, (2) make statistical choices regarding the trade-off between match quality and representativity and (3) automatically generate a ground truth of true and false matches, suitable for training purposes, based on networked family relationships. Given the recent availability of hundreds of millions of digitized census records, this algorithm significantly reduces computational costs to researchers while allowing them to tailor their matching design towards their research question at hand (e.g. prioritizing external validity over match quality). Applied to U.S Census Records from 1850 to 1940, the algorithm produces two sets of matches, one designed for representativity and one designed to maximize the number of matched individuals. At the same level of accuracy as commonly used methods, the algorithm tends to have a higher level of representativity and a larger pool of matches. The algorithm also allows one to match harder-to-match groups with less bias (e.g. women whose names tend to change over time due to marriage).Version of Recor
