Electoral and Demographic Data for New York, 1830-1875

Benson, Lee; Silbey, Joel H.

doi:10.3886/icpsr06926.v1

Cited by 2 publications

(3 citation statements)

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“…We focus attention on three elections and one referendum in New York State during the mid-1840s: the 1842 Gubernatorial election, the 1844 Gubernatorial election, the 1844 Presidential election, and an 1846 referendum on African American suffrage as reported by Benson and Silbey (2002). Their dataset provides us with a rare view of town-level measures of voter turnout, whereas most sources for this period only report county-level measures.…”

Section: Data On Political Participationmentioning

confidence: 99%

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Foundations of a New Democracy: Schooling, Inequality, and Voting in the Early Republic

2022

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Democratic theorists have long argued that states can create more resilient democracies through education. Educational investments are thought to produce more economic equality and instill in citizens greater capacity and responsibility to participate in politics. Using a geographic regression discontinuity design and township-level data from Antebellum New York State, we examine whether state funding for common schools led to higher voter turnout as well as higher earnings and lower inequality. Our estimates support the view that a participatory democratic culture emerged not only because of initial favorable endowments but also because of subsequent government decisions to fund education. New York townships that received more school funding later had higher median earnings, lower earnings inequality, and higher levels of voter turnout. Our findings support the view that maintaining democracy requires active investments by the state, something that has important implications for other places and other times—including today.

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Section: Data On Political Participationmentioning

confidence: 99%

“…The variable 1846 Pro Suffrage is equal to the percentage of voters favoring extending suffrage by abolishing a property requirement for African Americans to vote. The source for these data is also Benson and Silbey (2002).…”

Section: Data On Political Participationmentioning

confidence: 99%

Foundations of a New Democracy: Schooling, Inequality, and Voting in the Early Republic

2022

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“…For the model used in UCINET based on MINRES [4,5], recalling (2) we note that an efficient approach is to recast the optimization problem into the computation of a matrix eigenvector, for which well-established algorithms are available.…”

Section: The Optimization Problemmentioning

confidence: 99%

A Nonlinear Spectral Method for Core--Periphery Detection in Networks

Tudisco¹,

Higham²

2019

SIAM Journal on Mathematics of Data Science

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We derive and analyse a new iterative algorithm for detecting network core-periphery structure. Using techniques in nonlinear Perron-Frobenius theory, we prove global convergence to the unique solution of a relaxed version of a natural discrete optimization problem. On sparse networks, the cost of each iteration scales linearly with the number of nodes, making the algorithm feasible for large-scale problems. We give an alternative interpretation of the algorithm from the perspective of maximum likelihood reordering of a new logistic core-periphery random graph model. This viewpoint also gives a new basis for quantitatively judging a core-periphery detection algorithm. We illustrate the algorithm on a range of synthetic and real networks, and show that it offers advantages over the current state-of-the-art.1. Motivation. Large, complex networks record pairwise interactions between components in a system. In many circumstances, we wish to summarize this wealth of information by extracting high-level information or visualizing key features. Two of the most important and well-studied tasks are• clustering, also known as community detection, where we attempt to subdivide a network into smaller modules such that nodes within each module share many connections and nodes in distinct modules share few connections, and • determination of centrality or rank, where we assign a nonnegative value to each node such that a larger value indicates a higher level of importance. A distinct but closely related problem is to assign each node to either the core or periphery in such a way that core nodes are strongly connected across the whole network whereas peripheral nodes are strongly connected only to core nodes; hence there are relatively weak periphery-periphery connections. More generally, we may wish to assign a non-negative value to each node, with a larger value indicating greater "coreness." The images in the centre and right of Figure 1 indicate the two-by-two block pattern associated with a core-periphery structure.The core-periphery concept emerged implicitly in the study of economic, social and scientific citation networks, and was formalized in a seminal paper of Borgatti and Everett [3]. A review of recent work on modeling and analyzing core-periphery structure, and related ideas in degree assortativity, rich-clubs and nested/bow-tie/onion networks, can be found in [9]. We focus here on the issue of detection: given a large complex network with nodes appearing in arbitrary order, can we discover, quantify and visualize any inherent core-periphery organization?In the next section, we set up our notation and discuss background material. Many detection algorithms can be motivated from an optimization perspective. In section 3 we use such an approach to define and justify the logistic core-periphery *

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Electoral and Demographic Data for New York, 1830-1875

Cited by 2 publications

References 0 publications

Foundations of a New Democracy: Schooling, Inequality, and Voting in the Early Republic

Foundations of a New Democracy: Schooling, Inequality, and Voting in the Early Republic

A Nonlinear Spectral Method for Core--Periphery Detection in Networks

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