About This Story

Our Data

There was no particular order to which we transitioned from source to source, our team’s workflow primarily involved independent research of different topics. As such the following sources will be organized by the topic of our project which they were applied to:

Racial Disparities

The execution database formed the basis for our project essentially. The DPIC website was one of the first sources for the death penalty that we came across and it more than provided for our initial start. We did not know fully what our narrative was going to be like at the time but examining the ethnographic data on the site prompted us to explore it further, subsequently allowing us to find out the complexity behind the issues surrounding capital punishment - we could finally flesh out our narrative. After developing the story a bit more, statistics were found to provide a better understanding of the historical, cultural, and legal relevance of racial disparities.

"Execution Database", Death Penalty Information Center:
- https://deathpenaltyinfo.org/executions/execution-database

"David C. Baldus, 75, Dies; Studied Race and the Law," Adam Liptak:
- https://www.nytimes.com/2011/06/15/us/15baldus.html
"DPIC Analysis: Racial Disparities Persisted in U.S. Death Sentences and Executions in 2019," DPIC:
- https://deathpenaltyinfo.org/news/dpic-analysis-racial-disparities-persisted-in-the-u-s-death-sentences-and-executions-in-2019

Efficacy

Efficacy became the natural next step in our narrative once we started coming across more story segments on the DPIC website. Luckily for us, we stumbled across the first article listed here: "Study: 88% of criminologists do not believe the death penalty is an effective deterrent". It linked us to two studies in 1996 and 2008 where criminology and legal experts were asked their various opinions and takes on the death penalty. Again, this source is coming from the DPIC website - in addition to the execution database, they serve as a general hub of articles and records for capital punishment for the public to dissect and learn more about the legal ruling. *Note that some cost articles can double as efficacy sources.

"Study: 88% of criminologists do not believe the death penalty is an effective deterrent", Death Penalty Information Center:
- https://deathpenaltyinfo.org/news/study-88-of-criminologists-do-not-believe-the-death-penalty-is-an-effective-deterrent
"Fall 1996 Deterrence and the Death Penalty: The Views of the Experts", Michael L. Radelet and Ronald L. Akers:
- https://scholarlycommons.law.northwestern.edu/cgi/viewcontent.cgi?article=6901&context=jclc
"Recent Developments Do Executions Lower Homicide Rates?: The Views of Leading Criminologists", Michael L. Radelet & Traci L. Lacock:
- https://files.deathpenaltyinfo.org/legacy/files/DeterrenceStudy2009.pdf

Financial Cost

After we concluded our exploration of efficacy, the natural next step for our progression was to begin looking into financial impact. However, this time around, the sheer scale of the DPIC website’s articles proved to be a bit more difficult to pinpoint specific enough resources regarding costs in a timely enough manner. As such we began exploring other resources across the web as we figured financial data would likely be in wide circulation anyways. Additionally adopting this research workflow opened up avenues for us to do extra analyses such as per capita comparisons because we weren’t just limiting ourselves to the one good source we found. The first source from World Prison Brief provided a couple decades worth of stats on the population data as well as prison admission rates based on the national population. This was used to further contextualize cost data provided by the second CA Legislative Analysts’ Office source, which helped us achieve a better understanding of the subcategorized costs that go into housing an inmate. From there the third and fourth sources came into play by helping to produce a comparative costs per capita bar plot; car capita data was gathered generally from a AAA insurance article from 2019 and then military per capita cost data was gathered from that statista link.

Population Data:

"Supreme Court to Consider When Juveniles May Get Life Without Parole", United States of America | World Prison Brief:
- https://www.prisonstudies.org/country/united-states-america

Cost Data:

“How Much Does It Cost to Incarcerate an Inmate?” Legislative Analyst's Office:
- https://lao.ca.gov/PolicyAreas/CJ/6_cj_inmatecost
“Average Annual Cost of New Vehicle Ownership.” AAA Analysis Helps Drivers Understand the True Cost of Car Ownership:
- https://www.aaa.com/autorepair/articles/average-annual-cost-of-new-vehicle-ownership
Duffin, Erin, “U.S. Defense Expenditures per Capita 2020.” Statista:
- https://www.statista.com/statistics/203090/defense-expenditures-of-the-us-per-capita/

Amadeo, Kimberly, “What Criminal Sentence Costs More: Death or Life in Prison?”
- https://www.thebalance.com/comparing-the-costs-of-death-penalty-vs-life-in-prison-4689874#citation-15
“INCARCERATION WITHIN AMERICAN AND NORDIC PRISONS: COMPARISON OF NATIONAL AND INTERNATIONAL POLICIES”
- http://www.dropoutprevention.org/engage-backup/incarceration-within-american-and-nordic-prisons/
“How Much Does it Cost to Incarcerate an Inmate?”
- https://lao.ca.gov/PolicyAreas/CJ/6_cj_inmatecost
“Annual Determination of Average Cost of Incarceration”
- https://www.federalregister.gov/documents/2018/04/30/2018-09062/annual-determination-of-average-cost-of-incarceration

Outliers and Restoration

Tying all the previous topics of our data story together, we pinpointed the outliers in the graph data and expanded on them. We noticed that there was an upsurge of federal government executions during 2020, and considering the socio-political layout of the time it was easy to decipher the cause for it (specifically, Trump administration’s political agenda and pandemic breakout). We concluded with a more resounding and intimate message meant to encourage the national trend towards the direction it was initially heading: away from punitive justice and towards restoration.

"Execution Database", Death Penalty Information Center:
- https://deathpenaltyinfo.org/executions/execution-database
"Federal government in 2020 executed more prisoners than all 50 states: Death penalty research group," Luke Barr:
- https://abcnews.go.com/Politics/federal-government-2020-executed-prisoners-50-states-death/story?id=74760588
"Despite recent federal flurry, number of U.S. executions is lowest since 1991," Tom Jackman:
- https://www.washingtonpost.com/nation/2020/12/16/us-executions-decline/
"What Happens to the Federal Death Penalty in a Biden Administration?," Madeleine Carlisle:
- https://time.com/5932811/death-penalty-abolition-joe-biden/
"Executions and Death Sentences Drop to Historic Lows in 2020, even as Federal Government Ramps Up Executions," Margot Friedman:
- https://files.deathpenaltyinfo.org/documents/pdf/DPIC-2020-YER-Press-Release.f1608069407.pdf
"The Federal Government Restarts Federal Executions Amid Procedural Concerns and a Pandemic," DPIC:
- https://deathpenaltyinfo.org/facts-and-research/dpic-reports/the-federal-governments-2019-attempt-to-restart-federal-executions-an-analysis

Regarding Transformations...

Not many “transformations” were made with the data we decided to use for our project - most of the sources did all the work in terms of data collection. The main things we did involved copy pasting the data into some kind of software to output a csv file we could work with. SAS was utilized for this purpose and subsequently we made four csv files of our data. Those csvs were then opened in RStudio where R-code was developed to generate respective plots for us to use in our narrative.

So in other words, transformations we performed involved: converting the existent data from the sources above into csv format via SAS, and then uploading those files to RStudio to R-code plots for us to use in this project.

Limitations, Problems, and other Misc. Notes

Problems with the Data: Why Our Analysis Has Gaps

Many of the limitations or problems pertaining to the data which we ran into revolved around the nature of the information surrounding the death penalty. It is a topic that naturally warrants a lot of need for contextualization and as such there were several instances where we became concerned about possibly overlooking context behind a trend we graphed or even in some cases underappreciating the context. Particularly we ran into this dilemma when we initially started working on the DPIC execution data - we’d be able to identify many noteworthy features of the plots (or so we thought) but didn’t necessarily have all the information we needed to elaborate on whether or not it was significant. Subsequently this significantly lengthened the amount of time we needed to take when conducting statistical analyses of our plots. At the end of the day though, even despite the amount of time we invested into the data, the nature of the expansiveness of the system capital punishment and the discouse behind it will always remain a obstacle that must be kept in mind when looking critically at our project here.

Other problems involve the blurring of the lines when it comes to data. Intrinsically some categorical variables are incredibly hard to quantify for analytical purposes, and at some point the ethics of data representation come into play. For instance, with the execution data we are looking at the deaths of real people for some indication of what ethnographic impact the death penalty is having in this nation. While there certainly is information we can objectively gather from this dataset, there is also something to be said about what the dataset doesn’t reveal. In regards to racial disparities, while we may be able to identify such a problem from the data, we don’t get to see the individual impact those systematic misgivings - we are forced to assume things socio-culturally as part of our analysis. This includes sociological information such as quality of life in places such as Nordic countries on the basis of rehabilitation, or discrepancies between federal capital punishment and state capital punishment.

Some other issues of data came from ideas of efficacy which, as said earlier, are not so easily quantifiable and are seen as less ethos-based as the numbers become based on notable people and their opinions rather than pure, unbiased numbers.

Additionally, a noteworthy aspect could be the incorporation of the Trump administration’s use of the death penalty at the end of 2020. Said aspect was a consequence of Trump’s last weeks in office and serves as a remarkable outlier for our data as a cluster of punishments were served consecutively.

Team Credits

Andrew Bissell

Major: Statistics and Data Science, 3rd Year
Responsible for making unique plots for the group to use on the project based on data we found, general project management and coordination.

Sabrina Elmoussaid

Major: Communications / Global Studies, 3rd Year
Responsible for developing on the data outliers and exploring a prospective transformation from punitive to restorative justice. Also found general data on capital punishment and specifically focused on exploring racial disparities.

Makenna Brown

Major: English, 3rd Year
Responsible for finding data about efficacy, finances, and some more broad information that could be applied to the project. Also created the skeleton and theme of the Wix site.

This data narrative project was created as an assignment for the course English 146DS, "Data Stories: Theory and Practice of Data-driven Narratives in the Digital Age" at UC Santa Barbara (Winter 2021).

Published under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

This data narrative project was officially completed:

March 15, 2021