University of Pittsburgh

Journal of World-Historical Information
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    38 research outputs found

    Complexities in Creating and Defining Topical Metadata Practices for a World-Historical Data Resource

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    Mobile Networks: Visualizing the Global Refugee Regime

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    This article identifies conceptual issues surrounding the visualization of refugee movement in relation to state borders. It argues that social-network-analysis software provides a tool for the creation of visualizations of human movement that are removed from geolocation. Such a method disassociates forced migration from preconceived notions about the importance of geographical proximity and the fixity of state borders. This article provides some brief examples of ways that these methods might be utilized to graph and visualize aspects of the global refugee regime. The global-scale, transnational conceptualization and new visualizations show networks of movement centered on new inter-state communities and highlights the role of non-state actors

    Col*Fusion: a Global-Scale Information Integration Infrastructure based on Crowdsourcing

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    The Slave Population in Pernambuco, Brazil, 1560-1872: A macrodemographic reconstruction

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    This paper exposes a demographic model to represent the evolution of the population of African slaves brought to the province of Pernambuco, Brazil, from 1560 to 1872, including their descendants. The main conclusion at this stage of the research is the confirmation that realistic combinations of mortality and fertility parameters, within the wide intervals acknowledged by the literature, do, in fact, generate populations in size and – more importantly – with the sex and age distributions uncovered in the first nation-wide census for Brazil, in 1872. Such combinations of parameters also reinforce the thesis that the slave trade was the main motor for the growth of the slave population and its descendants.

    Little Data Streams to the Big Data River: Data-Based Solutions to Non-Data Questions and Their Implications for the CHIA Project

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    This article offers an example of how a “traditional” reading of an historical text can invite, and be enhanced by, a data-driven analysis. It suggests that historians who do not work primarily in data keep in mind the possibility that their research, viewed from the correct angle, may contribute to the collection of world-historical data. The data on the National Hungarian Weekend Association, overwhelmingly qualitative, nonetheless permitted construction of a useful dataset. The social composition of leadership in the organization revealed an unexpectedly narrow and clear pattern through an orderly investigation of organizational registration lists.

    Large-scale data on U.S. disease, 1887 – 2014

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    Data, Set, Match: Reflections on Database History

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    Demographic Models for Projecting Population and Migration: Methods for African Historical Analysis

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    This study presents methods for projecting population and migration over time in cases were empirical data are missing or undependable. The methods are useful for cases in which the researcher has details of population size and structure for a limited period of time (most obviously, the end point), with scattered evidence on other times. It enables estimation of population size, including its structure in age, sex, and status, either forward or backward in time. The program keeps track of all the details. The calculated data can be reported or sampled and compared to empirical findings at various times and places to expected values based on other procedures of estimation. The application of these general methods that is developed here is the projection of African populations backwards in time from 1950, since 1950 is the first date for which consistently strong demographic estimates are available for national-level populations all over the African continent. The models give particular attention to migration through enslavement, which was highly important in Africa from 1650 to 1900. Details include a sensitivity analysis showing relative significance of input variables and techniques for calibrating various dimensions of the projection with each other. These same methods may be applicable to quite different historical situations, as long as the data conform in structure to those considered here

    From Financial Crash to Debt Crisis

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    Introduction: Historical Databases in Process

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