Gender, Jail, and Injustice: Gender Interaction Effects on Judicial Sentencing Rhetoric

The posts below are brief summaries of 14-week research projects designed and carried out by our student team. tPP plans to release the full studies as peer-reviewed publications in the future.

Gender, Jail, and Injustice: Gender Interaction Effects on Judicial Sentencing Rhetoric

Maddie Weaver & Alexandria Doty








The following report analyzes court documents that correspond with the Prosecution Project’s dataset as of mid-April 2019. There is a clear and statistically significant relationship between gender and sentence lengths, but there are no prevailing theories on the reasons behind this correlation. The purpose of this study was to find out why defendants that have similar backgrounds in all other coded variables still face different sentences, as decided by a judge through the federal sentencing guidelines. There is no written record of how a judge uses the guidelines or any other logic for that matter to show how they reach the sentence that they do. We wanted to find the patterns between how sentences are given and connect it with the rhetoric that judges use during sentencing hearings for both men and women. It was hypothesized that, when analyzing judge’s sentencing transcripts, there will be gender-based biases within the rhetoric.

The final sentencing hearing is focused on giving both the prosecuting witness(es) and the defendant a space to express the effects of the crime and the trial on their lives. Federal judges are elected or appointed to be impartial upholders of the law, but as shown by the creation of the Federal Sentencing Guidelines, impartiality is something not commonly achieved. Thus, we believed that we would be most likely to find consistent rhetoric used by judges by utilizing sentencing hearings. Our study looked at the transcripts published from these hearings, as well as other documentation related to sentencing such as memorandums and judgements, in order to collect data of the lexicon and rhetoric used.

The hearing transcripts from 54 women within tPP database were analyzed and then compared to a comparable sample of men to look for major differences or patterns that were present. We analyzed these documents through AntConc, a corpus linguistic analysis software that allows us to look into patterns present in large selections of text and found many interesting patterns.

One interesting finding was through another software we used, R, that showed men’s memorandums being shockingly similar to women’s judgments when it came to the ratio of positive and negative words used throughout the document. Similarly, men’s judgments were very similar to women’s memorandums ratio of positive to negative words. While all had significantly more negative than positive words, the men’s judgments had the most positive to negative ratio, just exceeding the half and half point.

With more time and expertise of R and other sentiment analysis packages, this research could dive deeper into finding what these patterns describe. If bias is found with closer examination by more advanced sentiment analysis, judges could be trained and better understand their bias as well as the bias of the Federal Sentencing Guidelines that could be leading men to receive disproportionally longer sentencing lengths. This could then be examined not only for gender but also inclusive of variables like race.

An Exploratory Dive into the Dark Network Links of Far-Right tPP Cases

The posts below are brief summaries of 14-week research projects designed and carried out by our student team. tPP plans to release the full studies as peer-reviewed publications in the future.

An Exploratory Dive into the Dark Network Links of Far-Right tPP Cases

Meg Drown

There has been a mass movement by far-right extremists to dark web social media platforms and the use of cryptocurrencies as a means to crowdsource. This move has largely been due to the initiatives of big tech companies to stymie the current of extremist content on their websites by removing users who express extremist views or are otherwise connected to extremist organizations. Many on the far-right have publicly renounced Facebook, Twitter, and other tech companies claiming that their actions to remove extremist content, especially that iterated from the far-right, infringes on Americans’ right to free speech [1].

Although there are detailed user agreements that place constraints on the content that is broadcast by users, prohibiting the kind of insulting and hateful speech that is often expressed by those on the far-right, leaders and organizers on the far-right have gained momentum by politicizing this phenomenon. However new sites have arisen to paradoxically give far-right extremists a “safe haven” to express their views. The creator of social media platform Gab, has told media outlets that the purpose of Gab was to create an online platform specifically for conservatives and the far-right, whom he believes have been treated unfairly by big tech. The site’s lackadaisical regulations on what would normatively be considered hate speech and its targeted advertising towards conservatives have combined to create the perfect storm, or what has been described as a “hate-filled echo chamber full of racism and conspiracy theories” [2].

Likewise, 8chan, an imageboard and offshoot of 4chan, is another well-known site that harbors extremist content. Purportedly, the manifesto released by 28-year-old Brenton Tarrant, the man who murdered 50 Muslims at two mosques in Christchurch, New Zealand was circulated via 8chan and fell into the hands of another impressionable extremist. John Earnest, a 19-year-old who has been indicted on 109 hate crime charges, carried out an attack on a synagogue in early May leaving one dead and three injured. According to a Vox article detailing the apparent perils of 8chan, Earnest was inspired to carry out the attack, in part, due to the radical ideology outlined in Tarrant’s manifesto [3].

Fintech has pursued similar action against extremist users. Mainstream digital fundraising sites such as PayPal and Amazon, have been proactively identifying and denying access to those users utilizing their sites to fundraise for nefarious purposes. Richard Spencer and prominent voices on the far-right reveled at the spectacularity of Bitcoin to fundraise for their unsettling online platforms. Bitcoin and other cryptocurrencies are unique due to their peer-to-peer (P2P) transactional features. It is, in part, due to this feature that makes it easy to hide under the guise of anonymity while extorting money for various purposes [4]. Though the apparent anonymity benefits of Bitcoin and other cryptocurrencies have been cited by law enforcement and those using Bitcoin as a means to fundraise as the defining feature of the platform, scholars have asserted that Bitcoin is one knock below anonymous. Rather, Bitcoin and many of its crypto counterparts are pseudonymous due to endpoint identification in straightforward transactions.

An ambition of many open-source intelligence analysts is to be able to identify and track the financial networks of far-right actors. Certainly, open-source intelligence analysts have been highly successful at identifying traditional transactional networks and, recently, crypto transactional networks. John Bambenek, an open-source intelligence researcher and professor of cybersecurity at the iSchool in Illinois, does just that [5]. Specifically, Bambenek tracks the donations received by white nationalist BTC wallets, the amount spent, and their balance, which he records in a daily wallet summary report via his Twitter account called Neonazi BTC Tracker (@NeonaziWallets) [6]. Bambenek also records whenever a withdrawal or a substantial donation is made to one of the white nationalist BTC wallets in a separate tweet. For all of the apparent anonymity benefits of using BTC, highly-skilled computer scientists are able to identify and track specific BTC wallets using mathematical algorithms and the fact that the BTC transaction log is public by design.

Keeping in mind tPP while researching the shift of far-right actors to cryptocurrencies and dark web platforms, it was an ambition of mine to be able to identify individuals who occur in tPP that exist in a crypto transactional network with some prominent members of the far-right that have rose to prominence in recent years, and have, in fact, gained traction in the Bitcoin and dark web realms. However, due to my limited capabilities in being able to identify users who send donations via Bitcoin to these prominent far-right actors and the sheer volume of transactions that occur between their accounts, I found it an improbable task to carry out in a limited amount of time.

However, I did find that individuals in tPP who are coded as Rightist: Identity-focused under the variable Ideological Affiliation, especially those occurring after the Charlottesville “Unite the Right” rally in 2017 had maintained a presence on dark web forums and were, perhaps, inspired by extremist media purveyed on these forums. Wanting to delve deeper into the dark web links of individuals in tPP, I took an exploratory sample of those coded as Rightist: Identity-focused occuring after 12 August 2017. I created a link analysis which identified how various actors in the exploratory sample connected with one another.

To do so, I collected open-source data on the individuals via court documents, newspaper articles, and examination of dark web content that had been released online. Though the results were rather underwhelming – most individuals who were linked to one another were linked through organizational ties – I did find that several members of my exploratory sample had maintained ties with prominent far-right organizers, such as Richard Spencer and Eli Mosley, or others in tPP who had carried out high-profile attacks such as Dylann Roof and Robert Bowers. In fact, Bowers purportedly decried the prosecutions of various members of the Rise Above Movement (RAM), described as a “a Southern California-based racist fight club” [7], who appeared in the exploratory sample and had allegedly interchanged with the leader of RAM, Robert Rundo, via Gab.

Though the subject sample was small and the findings marginally supportive of a dark web network that exists between tPP individuals, my paper revealed that there are demonstrable links between actors on the right through dark web social media platforms such as Gab, Discord, and 8chan. Further studies can and should be carried out in order that we can better understand how individuals occurring in tPP interact and position themselves in the far-right movement through dark web participation.


[1] Kirkland, “Relegated To Fringe Platforms, White Nationalists Stuck In Own Echo Chamber”; “Big Tech, the Alt-Right and the Unknown Future of the Internet”; “Inside the Hate-Filled Echo Chamber of Racism and Conspiracy Theories | Media | The Guardian.”

[2] “Inside the Hate-Filled Echo Chamber of Racism and Conspiracy Theories | Media | The Guardian.”

[3] Stewart, “8chan, Explained.”

[4] Mabunda, “Cryptocurrency.”

[5] Matsakis, Koebler, and Pearson, “This Twitter Bot Tracks Neo-Nazi Bitcoin Transactions.”

[6] Tracker, “New Payment to Henrik Palmgren (Http://RedIce.Tv ): 0.00519921 BTC ($20.16) Https://Blockchain.Info/Tx/127b726aa6ad4c43d41b1b6783d1a71e05c27deeae7a393b44ced91a032948a7 … Total of Henrik Palmgren (Http://RedIce.Tv ) BTC Wallets: 0 BTC ($0).”

[7] “Rise Above Movement.”

Friend of Foe?: An Analysis of Factors Influencing Sentence Length in the Prosecution of Terrorism

The posts below are brief summaries of 14-week research projects designed and carried out by our student team. tPP plans to release the full studies as peer-reviewed publications in the future.

Friend of Foe?: An Analysis of Factors Influencing Sentence Length in the Prosecution of Terrorism

Megan Burtis & Liz Butler

Our research project utilized a grounded theory case study analysis to determine which factors influence the extent to which the Federal Sentencing Guidelines are adhered to in the prosecution of terroristic cases.

The cases we analyzed we United States v. Burgert et al., United States v. Boyd et al., and United States v. Dibee et al. All findings within our paper were the result of the analysis of the three case studies we selected. Using a grounded theory approach, the analysis of these findings yielded the creation of specific categories which provide a theory as to what factors have the greatest impact on sentencing. Our paper theorizes that government manipulation of the Federal Sentencing Guidelines plays the biggest role in determining the final sentence length of defendants prosecuted for terroristic crimes. Thus, the way in which the government views a defendant ultimately determines their sentence.

Four key factors were found to influence the government’s view of defendants which include the plea entered by the defendant, the level of regret the defendant shows for the crime committed, the degree to which the defendant continues to support the ideology which motivated their crime, and finally the extent to which the defendant cooperated with the government during both the investigation and adjudication. The evaluation of these factors allowed for defendants to be placed in specific categories, as shown in the table, which reflect whether they will receive sentences at the lower or higher end of what was recommended.

Our research tentatively supported our initial hypothesis that race/ethnicity, citizenship status, and “othered” status would be influential factors, but we would require more evidence to make this claim with any degree of certainty. Finally, these findings have significant implications for future research, specifically pertaining to the use of terrorism enhancements and plea bargains. Further research is recommended to see whether both or neither of these strategies are suitable as a counterterrorism measure. Further research into the generalizability of our theory will also be required to test its applicability.

Deportation Station: How the United States Decides Who Stays and Who Goes

The posts below are brief summaries of 14-week research projects designed and carried out by our student team. tPP plans to release the full studies as peer-reviewed publications in the future.

Deportation Station: How the United States Decides Who Stays and Who Goes

Zoe Belford

My paper assessed what conditions lead to an increased likelihood of deportation following a guilty verdict in a United States terrorism prosecution, as well as if and how this relates to post-9/11 national security policy.  My sample included all cases in the Prosecution Project’s database that included a defendant with foreign citizenship, as well as had ended in a guilty verdict. This resulted in a sample size of 306, which I divided into two subsamples – cases which ended in deportation and cases which did not. Using these two samples,  I conducted a descriptive statistical analysis to find if any notable differences existed between the two groups.

My findings were as follows. Compared to non-deported defendants, deported defendants were:

    • Less likely to have a case involving a co-defendant
    • Less likely to have been charged with a previous similar crime
    • More likely to have completed the crime they were charged with
    • Less likely to have their case involve an informant
    • Less likely to be affiliated with a foreign terrorist organization
    • Have, on average, significantly lower sentence lengths
    • More likely to have an unclear ideological affiliation
    • Less likely to have an affiliation with a Salafi/Jihadist ideology
    • More likely to be Middle Eastern/North African

All of these findings hold the potential for further research, but I focused on the variable of foreign terrorist organization (FTO) affiliation. I found that deported defendants are known to be FTO-affiliated in only 35% of cases, whereas non-deported defendants are known to be FTO-affiliated in 72% of cases.

During my research for this project, I came across a theory that seemed particularly applicable to my observed findings. Based in economic and national security studies, mosaic theory posits that bits of intelligence can be pieced together by hostile parties (i.e. foreign intelligence agencies, foreign terrorist organizations) to form a picture of US intelligence practices and knowledge [1]. Since 9/11, this theory has played a significant role in the United States court system. Specifically, it was used to justify the classification of documents regarding the detainment of over seven-hundred people in regards to September 11th [2]. Based on my findings, I hypothesize that that the government is choosing to keep defendants who are more intertwined with known terrorist organizations within the country to avoid the potential intelligence risks of a deportation hearing. Deportation hearings can only be closed in a select number of circumstances [3], whereas the precedent to use mosaic theory to justify the classification of criminal proceedings has already been set.


[1] Neuman, Gerald L. 2005. “Discretionary Deportation.” Georgetown Immigration Law Journal 20: 611–56.

[2] Pozen, David E., James E. Baker, Jessica Bulman-Pozen, Fadi Hanna, Kenneth Levit, John Sims, and David Vladeck. 2005. “The Mosaic Theory, National Security, and the Freedom of Information Act.” Yale Law Journal.

[3] “Fact Sheet: Observing Immigration Court Hearings.” 2015. Department of Justice. February 10, 2015.