Featured Publications

This article analyzes a unique panel data set to assess the effect of militarism on per capita carbon dioxide emissions. We extend previous research examining the effects of military expenditures on carbon emissions by including in our analyses over 30 years of additional data. In addition, we compare our preliminary results to those obtained from other estimation procedures. Specifically, we report and visually illustrate the results of 54 cross-sectional models (one for each year) and 36 unique panel regression models on both balanced and unbalanced panels. We assess how this relationship has changed over time by testing for interactions between military spending and time and by systematically re-analyzing our data across 180 panel regressions with varying time frames. A strong and enduring association between military spending and per capita carbon emissions is indicated in cross-sectional comparisons. Our panel analyses reveal a much weaker and varying relationship that has become stronger in recent decades. Moreover, we find that the effect of military spending on per capita carbon emissions is moderated by countries’ level of economic development, with military spending of more wealthy countries having relatively larger net effects on carbon emissions. We partially confirm previous findings on the temporal stability of the environmental impacts of militarism. Our analyses show, however, that this temporal stability has emerged relatively recently, and that the relationship between military expenditures and carbon emissions is weaker prior to the 1990s.
Journal of World Systems Research, (forthcoming 2017)

Publications

  • The Treadmill of Destruction in Comparative Perspective: A Panel Study of Military Spending and Carbon Emissions, 1960-2014.

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  • The Treadmill of Destruction and Ecological Exchange in Comparative Perspective: A Panel Study of the Biological Capacity of Nations, 1961-2007

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  • Explaining Social Action Revisited: A Reply to John Levi Martin

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  • Explaining Explanation: A Critical Review of John Levi Martin’s The Explanation of Social Action

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  • Communication, Language, and the Emergence of Social Orders

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Talks & Presentations

Data & Visualizations

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Fatal Police Shootings (2013-2016) & County Level Data

This is a set of csv files including a number of variables including fatal police shootings and other crime and socioeconomic covariates at different levels of geographical aggregation from 2013-2016.

Police Shooting

Police Shooting Demographics

Recent Posts

I’ve made the following county-level graphs of fatal police shooting rates by race using data from the Census and compiled from the data I’ve now made available on figshare: Bradford, John Hamilton (2017): Fatal Police Shootings (2013-2016) & County Level Data. figshare. Below is the graph. I. Loading Data 1. A function to retrieve state abbreviations getState.abb <- function(x){ ##remove punctuation and twim white space, convert to lower case x <- tolower(trimws(gsub("[[:punct:]]", "", x))) x[which(x == "washington dc")] <- "district of columbia" states.

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I’ve just published new data sets to figshare with accompaying code to RPubs. Below is the project description with links. This is a set of csv files including a number of variables including fatal police shootings and other crime and socioeconomic covariates at different levels of geographical aggregation from 2013-2016. Five of the files use only the Washington Post data covering years 2015 and 2016, whereas the other five files utilize fatal police shootings of civilians for years 2013-2016, combining the Lott & Moody (2016) data for years 2013-2015 and Washington Post data for 2016.

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A new article has just been published in the Journal of Criminal Justice, “The prevalence of fatal police shootings by U.S. police, 2015–2016: Patterns and answers from a new data set” by Shane, Lawton, and Swenson (2017) . The authors make some good points that I mostly agree with, but I cannot make sense of their finding that the mean rate of black civilians killed by police (per 100,000) is lower than that of whites.

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Below are some new county-level heat maps of police shooting data, compiled from the Lott & Moody (2016) data for years 2013-2015, and the Washington Post for 2016. Below the graphs, the R code is provided. Figure 1. Frequency of Civilians Killed by Police per County Figure 2. Civilians Killed by Police per 100,000 Residents Figure 3. Killed by Police Rates for Larger Counties R Code 1. Load the Data.

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Scatterplot - Violent Crime & Population by Race: Police Killings vs No Police Killings of Civilians. (Washington Post)

jhbradford

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