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  You are Here:    Home          Analyses Results

Analyses Results

It’s tremendously important to the credibility of my report that I present everyone with the results of my analyses. This is a particularly Herculean task because of the immensity of the data, tables, graphs, and so forth. Consequently, this will require a great deal of time and effort on my part. It is currently my top priority. As such, this section will be updated regularly. Continue checking back for updates and sign up for my newsletter to receive updates by email.

The data set I’ve chosen to publicly share for the time-being primarily surrounds certain persons of interest that were chosen because of analyses results. More explanation of this process can be found in my “Current State of Affairs” and Methodology sections. There are numerous other directions I will take. You can download my select data set of content here.

Before moving into the nitty gritty data, you may want to first take a look at my infographics. I developed these after an enormous amount of analyses and interpretations of results. You can find a field map and and interactive visual module HERE.

Results of Content Analyses 1

July 2, 2022

My first analysis coded the data thematically based on word similarity, occurrence, and the sentiments scaffolding those words. What this provides is a broader view of the kinds of actors, their activities, the entities involved, and so forth. In other words, this gives us a broad ‘feel’ of the nature of the kinds and qualities of the social identities with which we are dealing: their norms, means of representation, networks, political and economic associations, role attribution, role expectations, and, overall, a greater grasp of the myriad elements that give shape to their social fields. I enjoy Foucault’s definitions with regards to these networks of intersubjectivities. He would suggest that we view it as episteme: a system of interacting concepts that define, give shape to, and give rise to particular groups over a particular period of time. For this investigation, a broad primary exploratory analysis provides data to employ through my theoretical frame to inform the next steps in data analysis. Here are the results presented as a cluster tree (fig. 1 – because it’s too large, it it cannot be displayed on this site and is only available here) and as a circle graph (fig. 2also available in high res here (because the image below is hard to read)).

Fig 2 – Circle Graph 1 – Items Clustered by Word Similarity – Activities.

These two visuals of the data inform the next steps for refining the data source. My faithful reader, think of these next steps in the way you would think of mining: your digging deeper to find gold; but in the case of research, avoiding biases are of the utmost importance. This is the point at which theoretical frames are of the greatest utility. Applying my theoretical frame to these data, I can form the following new exploratory inquiries:

  • Q1 – Who are the primary actors involved in all of these bankruptcies?
  • Q2 – How and why were they involved?
  • Q3 – What entities (studios, government, or otherwise) are involved?
  • Q4 – What are the allegations that are salient in these data; who is making them; and against whom?

Persons Involved

From the above thematic coding and by relying on my theoretical frame I can refine the dataset by performing word frequencies and remove irrelevant words to refine my search. During these decision-making processes, I assure you that relevancy is determined by the guiding principles of sound theory. I performed this function and limited it to the top 30 most frequent words. I present to you a frequency table (fig. 3), a cluster tree (fig. 4), and four circle graphs. The first circle graph shows strong thematic similarity of the occurrences of particular words (fig. 5 – between p>0.5 and p=1.0). The second circle graph shows weak thematic similarity of the occurrences of particular words (fig. 6 – between p<0.5 and p>0.0). Since there was no strong dissimilarity (p<-0.3), the third circle graph shows moderate dissimilarity (fig. 7 – p<-0.1) and the fourth circle graph shows all dissimilarity (p<0.0).

Fig. 3 – Frequency of Occurrences of Particular Words – 30 Word Count.
Fig. 4 – Cluster Tree Displaying Thematic Similarity of the Occurrences of Particular Words – 30 Word Count
Fig 5 – Circle Graph 2 – Strong Thematic Similarity of Occurrences of Particular Words – 30 Word Count – (between p>0.5 and p=1.0)
Fig. 6 – Circle Graph 3 – Weak Thematic Similarity of Particular Words – 30 Word Count – (between p<0.5 and p>0.0)
Fig. 7 – Moderate Thematic Dissimilarity of the Occurrences of Words – 30 Word Count – (fig. 7 – p< -0.1)
Fig. 8 – All Thematic Dissimilarity of the Occurrences of Words – 30 Word Count – (p<0.0)

Analysis of Persons and Entities Involved

I turn now to explain my analyses of these results and how it informs the next step in the research process. First, I must explain how I’ve refined my theory and methods from the above analyses. Observing the first cluster tree and circle graph and applying Dynamic Social Network Theory gives shape to and a grasp of the following for consideration:

  • The rough forms of various social fields and contents of the episteme;
  • The differences between these fields in terms of access to various kinds of capital;
  • The effects of ideologically-based homophily;
  • How the behaviors of members of particular groups can be predicted by:
    • Perceived competition with some other group;
    • Proximity to members of the perceived ingroup and any other perceived outgroup;
    • Access to resources;
    • Subcultural norms and repertoires;

This is the fun part for an uber-geek like me: applying theory to interpret data. In this case, social fields are identifiable in terms of the ways in which the data appears after it’s been thematically coded and compiled. The frequency of occurrences of theme or sentiment can parse out particular persons, places, and things in such a way that we gain purchase on a broader view of the kinds of social bridges being built and a glimpse into the possibilities for the motivations behind those processes. By applying Social Identity Theory, we can quite easily understand that cases of interpersonal violence, domestic violence, or sexual assault, tend to be highly gendered and, consequently, gendered social identities play an enormous role within the dynamics of each case, how its perceived by the public, the ways in which its handled by a Justice system, and, thus, the outcomes within and across these overlapping social networks or fields.

With these conceptual and theoretical refinements that are based off rigorously analyzed data, an inspection of individual and group behaviors and interactions becomes much more fruitful. It becomes clear that a number of holding firms, media production companies, and hedge-fund billionaires were involved. These relationships between and within this particular social field also involved numerous bankruptcies, shifting social roles, various financing opportunities, and exchanges of various capitals. Attached to all of these social fields is the gendered episteme I mentioned previously; that is, the perceived difference in access to opportunities between groups. In manifest reality, we can observe this in terms of the interplay between the #MeToo movement, the victim identity imposed on women, and the tremendous social support it receives. It is not an arguable premise to believe that this episteme would also inform and be informed by the cultural repertoires of wealthy financiers, movie stars, and so forth. Following from this and drawing from Differential Association, Differential Identification, and Differential Opportunity theories, it is not a stretch to suggest that the affluent actors within these interaction rituals would be most interested in exchanging definitions of norms that favor capital accumulation regardless of whether or not these violate the law. Consequently, we can safely assume that those persons are best-suited to gradually refine, over time, better and better strategies for opportunities for accessing capital. I believe that I’ve made it clear, faithful reader, that the nexus of social fields that is the chimera of the #MeToo movement and Radical Feminism created a new opportunity structure for associates to strategize exercising methods of control over the access to, exchange of, and distribution of various capitals.

Bringing my analysis to an interpersonal level, I want to begin by discussing individual actor’s actions and the possible motives behind them, the social bridges burnt or built, the ways in which biopower applies, the differences in the availability of opportunities or access to resources, and individual social identification processes.

Ryan Kavanaugh

For more information on Ryan, you can turn to my internal page, to Wikipedia, or to iMDb. While information from these sources informed my investigation, it was only insofar as to provide further possibilities for motivations and behaviors. My foundational sources can be found on my Bibliography page. Turning from the very broad view I’ve outlined above to a fine-toothed comb on an individual-level, I am most interested in the particular ways in which actors are involved with the social fields surrounding this case. Thus, it is of particular interest that Mr. Kavanaugh was the founder and CEO of Relativity Media, which, as you can see, dear reader, is also intimately involved throughout the data I’ve collected.

In 2018, an arbitration judge awarded Adam Fields, a co-president of Relativity, $8.44 million dollars for a complex false allegation hoax against him.



Myriad emails and memos had been exchanged among Relativity staff that revealed how these allegations from seven different women were false. In effect, “Relativity and Mr. Kavanaugh tried to exploit the #MeToo movement to destroy Mr. Fields’ reputation with false and fabricated accusations”. Although there was no evidence that tied Mr. Kavanaugh directly to the complex set of interaction rituals that led to this attempted hoax, there were numerous emails between staff with meta data that indicated that they were sent by a user named “KavKav”; a nickname by which he is colloquially known. If we remain true to the theories of social learning outlined in this work, this aspect of Mr. Kavanaugh’s cultural repertoire did not emerge from nowhere but, instead, must have been learned through social processes. Through the set of social exchanges making up Mr. Kavanaugh’s social network most assuredly floated the notion of weaponizing false allegations regardless of whether or not it violates the law. The question would be, “Why?”

Perhaps we can gain a better grasp on answering this question by examining the other actors in the network involved with this particular case. Mr. Kavanaugh was close friends and business associates with Harvey Weinstein. Since this work focuses on networks and identities, I’d like to first discuss Mr. Kavanaugh’s relationship with Mr. Weinstein and other associates before moving on to an analysis of Harvey. The reason for this will become clear, dear reader, if you are now approaching this with social learning in mind. If you weren’t already aware, Harvey Weinstein was found guilty of rape and sentenced to 23 years in prison; among the wide variety of other allegations and charges that he faces. Bear in mind that this is how this is being reported by the mainstream media, so take it with a grain of salt.



The images on the right are just a few examples of how Relativity and Mr. Kavanaugh were tied to Mr. Weinstein’s 2018 bankruptcy. What’s more, it would seem that the exchange of subcultural norms surrounding the practice of bankruptcies were transmitted during the interactions between Mr. Weinstein and Mr. Kavanaugh. I say this because when Relativity filed for bankruptcy in 2015, there were a number of Holding firms on the CH 11 record that belonged to Mr. Kavanaugh, including Knight Capital and Global Capital, as well as a separate holding firm under the name UltraV Holdings.

What’s more, Ballard Spahr LLP also appears in Mr. Weinstein’s bankruptcy. You can read my internal page for more information on them, but what’s important with respect to my investigation is how they are also tied to Weinstein’s bankruptcy. On the left you can see the two individuals on the Master Service List. It’s important to note that Ballard Spahr were the representatives on record for the Order to stop the testimony of TMZ employee, Morgan Tremaine.

Another very important entity named on Mr. Weinstein’s bankruptcy is Allred, Maroko, & Goldberg, who represented Charlotte Lewis in her sexual abuse allegations that were leveled against Roman Polanski. Again, faithful reader, I ask that you bear in mind the processes of social learning and the ways in which interactors provide one another with identity content and definitions for behavior. If you recall, Mr. Depp defended Mr. Polanski.

I must also point out that Mr. Kavanaugh produced Zombieland and 3 Days to Kill, both of which featured Amber Heard. He also handed her the “Rising Star” Award at the Texas Film Awards in 2014. Read more on that on the Amber Heard page. Amber’s involvement within and between these social fields is important to discuss, which I do in separate sections of this work. But here are the two of them at the award show.



It’s also very important for me to point out that it is well known that Mr. Kavanaugh has often used TMZ for his media drops of information regarding Relativity‘s films, Triller’s boxing events, and so forth. Allow me, dear reader, to outline another set of popular events that would receive publicity and thus greater social capital through TMZ’s forceful and sensationalized reporting: Art of Elysium galas. Here is one of many examples:



I believe that this is important to note because alongside Jennifer Howell at the Art of Elysium was their acting Chair of the Board, Mr. Kavanaugh. What’s more, although Disney bought most of FOX in 2020, prior to that Rupert Murdoch owned FOX, which is the parent company of TMZ. Mr. Kavanaugh’s social network also consists of his creation of Proxicoin, a secure cryptocurrency platform. Proxicoin was developed out of a $100 million dollar investment from Coinbase, which funds the Madison Group, a political lobbying group who’s efforts have been directed towards Donald Trump. What’s more, alongside Coinbase in supporting the Madison Group is another notable company, Cerberus Capital. Knight Global, Mr. Kavanaugh’s family investment firm, deals directly with Cerberus and makes their own ‘donations’ to political parties as well.



The CEO of Cerberus Capital is Stephen Feinberg, who served on Donald Trump’s Intelligence Board and is considered a top military contractor, having run the Freedom Group which produced some of the first AR-15s on the market.



Faithful reader, I believe that my architecture of these social fields ought to be clear and the variety of social exchanges of norms and values cast in stark relief. Throughout this network, different associations inform the available opportunities and repertoires for interactions between actors, the content of which are shaped by the dominant episteme. In this case, it would seem clear that a biopolitical and economic agenda took shape as the ritualized interactions between actors contained content that increasingly recognized how the status characteristic “woman” could be instrumentalized to exercise biopower over opportunities for access to capital. What’s more, when an opportunity to exercise this kind of power is made available, opportunities for alternatives crystallize into obsolescence when compared against a cultural repertoire that increasingly consists of affluence and deviations from publicly consensual norms.

Having adequately addressed and begun a sketch of Mr. Kavanaugh in relation to my investigation, I believe it is important to turn my attention to other actors.

Harvey Weinstein

To investigate other actors I was required to refine my data set and my approach to analyses. Consequently, I began by removing those words that referred to Mr. Kavanaugh and Relativity Media. I was also faced with removing other words that were not relevant to this investigation. Again, dear reader, I assure you that this decision-making process relied on sound theory. My results are telling. Below is a new word frequency table of my results from the above process (fig. 9). After performing a frequency query, I performed a cluster analysis on the data as well. Results for this analysis are displayed below in circle graphs, the first showing strong similarity (between p>0.5 and p=1.0 – fig. 10), the second illustrating weak levels of similarity (p>0.0 and p<0.5 – fig. 11), the third showing weak levels of dissimilarity (p<0.0 and >-0.1 – fig. 12), and, finally, the fourth that displays moderate levels of dissimilarity (p<-0.1 – fig. 13).

Fig. 9 – Frequency of Occurrences of Particular Words – 30 Word Count.
Fig 10 – Circle Graph 5 – Strong Thematic Similarity of Occurrences of Particular Words – 30 Word Count – (between p>0.5 and p=1.0)
Fig. 11 – Circle Graph 5 – Weak Thematic Similarity of Particular Words – 30 Word Count – (between p<0.5 and p>0.0)
Fig. 12 – Weak Dissimilarity of the Occurrences of Words – 30 Word Count – (p<0.0 but p >-0.01)
Fig. 13 – Moderate Dissimilarity of the Occurrences of Words – 30 Word Count – (p<-0.01)

To interpret these analyses I rely on sound theory. In this case, Granovetter’s concept of the strength of weak ties. I must first assert, dear reader, the importance of understanding dissimilarity. Stronger levels of dissimilarity indicate that the thematic occurrence of particular words are still related but distinct in sentimental tone. This is important to understand, friends, as it indicates that they are associated but thematically distinct. That is, throughout the data, Amber is associated with “investments”, “millions”, and “Weinstein”, but the occurrences of these words are scaffolded in sentimental tones that are distinct from one another. It’s a difficult concept to grasp, but I believe that I can illustrate this better by continuing with my discussion of Mr. Weinstein.

As I mentioned before, Mr. Weinstein was convicted of rape and sentenced to 23 years in prison. He is currently jailed in California and is awaiting trial on charges that he assaulted five other women.



I’ve also shared with you that Mr. Weinstein and Mr. Kavanaugh were close friends and intimately connected business associates. Below are a few images that support this assertion. The first image is a tweet captured in August of 2016 (fig. 14) and the second is a photo of Mr. Kavanaugh kissing Mr. Weinstein at an event (fig. 15).


fig. 14 – Tweet by Ryan Kavanaugh in 2016
fig. 15 – Ryan Kavanaugh and Harvey Weinstein

These men are incredibly wealthy in terms of their capital investments. Each are worth millions and millions of dollars. A cluster analysis of these two men alone would undoubtedly show a strong thematic similarity with the words “investment” and “millions”. They had both been deeply involved in the film and financing industries for years. Amber Heard, on the other hand, was on the rise. Her net worth was not comparable. Thus, any mention of “investment” or “millions” in relation to Ms. Heard would be in reference to her films, their producers, and other actors and entities involved. Those other actors and entities are discussed in different sentimental tones but are still tied to Ms. Heard. To provide you a simple example that will clearly illustrate the strength of weak ties with relation to my circle graph visualization of the strength of dissimilarity, you need to only look as far as the reviews for the movie “3 Days to Kill”. Critics were not pleased with Ms. Heard’s performance and my thematic coding would capture this negative sentiment. Alongside this, my thematic coding would capture that Mr. Kavanaugh was the producer and qualify this as a positive sentiment. Thus, they’re connected, but distinct in tone. This illustrates how my analysis captures the strength of weak ties. Throughout my data, there is clearly a similar weak tie between Ms. Heard and Mr. Weinstein as illustrated in fig. 13.

There is plenty of evidence and testimony that proves Mr. Weinstein is guilty of multiple criminal acts. I’m more than certain that he committed more crimes than we are aware of. With that said, staying true to the sound theories set out plainly in this work, the possibilities available for the contents of these actors’ individual identities would be limited to the available cultural repertoires and social fields within which these actors interacted. That’s a fancy way of saying that individuals learn behaviors from other individuals within the confines of social spaces. Particular behaviors cannot appear from nowhere. They are learned. Consequently, they are learned through engagement with other actors within the confines of particular social milieus, that is to say, within the overlapping social fields of interactors. Two men who are best friends and business associates. One who has been found guilty of sexual predation crimes and the other found to have generated a false allegation hoax leveled against one of his executives. All under the auspices of the growing #MeToo movement that was slowly being hijacked and corrupted by the likes of Michelle Dauber and other nefarious actors, including Amber Heard and Evan Rachel Wood. With these connections in mind, the intersubjective math becomes clear.

Needless to say, it is not arguable that Mr. Depp was the target of a coordinated attack fueled by the venomous #MeToo movement. What I hope that you are seeing, dear reader, is that the actors and entities involved in, that is, the network that gave momentum to and benefited from the #MeToo movement are interconnected financiers invested in everything from cryptocurrencies to firearms. Therefore, I refine my data set and process of analysis accordingly to continue to tease out particular actors and entities. I believe that it would be most suitable to turn my attention to an investigation of the Murdoch family. Primarily, Rupert and his son James. In addition to teasing out associations with the Murdochs, the rise in salience of the name “Epstein” demanded that I broaden my data set to include those articles referring to Epstein that I may have previously excluded due to relevance. This new refined data set (n=246) can be downloaded below.

Rupert Murdoch

As discussed above, I included new content while also excluding irrelevant words during the process of running frequency queries and cluster analyses. This allows a researcher to tease out different relationships by removing possibly confounding interactions between and among items being analyzed. In other words, to more clearly see the relationships between particular items it is necessary to remove items that reduce clarity due to irrelevance. First, I assure you again that these decisions were based off sound theory and methodology. Second, these exclusions don’t affect the process of coding thematic or sentimental patterns of items and their relationships to other items. One last change: I updated my query to display the 40 most frequent words, as opposed to 30, as I had done previously. The reason for this is because when lists become more and more exclusionary, there are fewer and fewer items of relevance. Now that I have made that clear, I present another frequency table (fig. 16). Below that is perhaps the most important cluster tree that I’ve ever produced (fig. 17). Take a look and you’ll see what I mean. Following the cluster graph are 4 circle graphs. Because I’ve chosen to include more items, these can get messy, so I’ve separated the p-values a little differently. They show strong similarity (fig. 18p>0.06 but p<1.0), moderate similarity (fig. 19p>0.03 but p<0.06), weak dissimilarity (fig. 20p<0.0 but p>-0.01), and, because there were no p-values below -0.02, I chose to display only moderately weak dissimilarity (fig. 21 – p<-0.01 but p>-0.02). Following that, I discuss Mr. Murdoch’s relevant background followed by an interpretation of the data below.


Fig. 16 – Frequency of the Occurrence of Words – 40 Word Count

Fig. 17 – Cluster Tree 4 – Word Frequency by Thematic Similarity – 40 Word Count

Fig. 18 – Strong Thematic Similarity – 40 Word Count
Fig. 19 – Moderate Thematic Similarity – 40 Word Count
Fig. 20 – Weak Thematic Similarity – 40 Word Count
Fig. 21 – Moderate Thematic Similarity – 40 Word Count

Before I address these data directly, it’s important to review those aspects of Mr. Murdoch’s history that are relevant to the present investigation. Anybody who followed the Depp v Heard case knows that Mr. Murdoch owns Newscorp and News Group Newspapers who own the Sun. You can read more about Mr. Murdoch on my internal page, on the Wikipedia page, or through Forbes. I discuss his connections to the other interactors within the heretofore mentioned social fields, entities, and movements. Of particular interest is the strength of his relationship with Harvey Weinstein. They were close enough associates that when Mr. Murdoch attended Mr. Weinstein’s 2008 wedding to Georgina Chapman, Mr. Murdoch’s 4-year-old granddaughter served as flower girl for the event.



Without a doubt, even the greatest philosophers in history could never deny that the core of humanity relies on that which is considered sacred; that is, that even those of us whom the rest of us might not consider good people still engage in ritualized interactions that the public consider sacramental. By having his daughter serve this role for Mr. Weinstein, Mr. Murdoch shows that this relationship is sacred to him, whatever that might mean. Regardless of his personal beliefs of the sacred, this certainly signifies that the ritualized interactions between these men must consist of exchanges of very intimate identity content. This content would obviously consist of their private beliefs and definitions of legality as it would apply to their particular social group. Between such individuals, the continued social facilitation of definitions of behavior that are favorable to capital accumulation functions in much the same way as classical or instrumental conditioning processes. That is, if rewards are postulated, garnered, shared, and so forth, then those definitions for behaviors are intensified regardless of whether or not they violate the law. What’s more, it is at this point of critical mass that individuals – especially in small groups – will innovate definitions of behavior. The #MeToo movement was just such an innovation in capital accumulation.

To properly outline the identity content that would have been exchanged during interactions with Mr. Murdoch, it’s important to observe his history of voracious and industrious corporate endeavors. In 1985, his company News Group Newspapers acquired Twentieth Century Fox Film Corporation, which would eventually evolve into the mass-media hegemon, FOX Corporation. The acquisition of FOX marked the beginning of Mr. Murdoch building a global media empire. Shortly thereafter, in 2005, Mr. Murdoch purchased MySpace and it’s parent company Intermix.



The same year, MySpace launched MySpace Records in a joint venture with Interscope Records.



It goes without saying that these kinds of business ventures happen during intimate ritualized interactions between powerful corporate actors. Marilyn Manson was originally signed by Trent Reznor to Nothing Records, which was a vanity label of Interscope Records. Due to poor sales, Manson parted ways with Interscope in 2009.



Faithful reader, I have already outlined the importance of considering how the exchanges of identity content and definitions for behaviors that occur within and between social fields give shape to the kinds of opportunities made available or obstructed. I have also outlined how identity content and definitions of behaviors are exchanged within and across these fields. As well, I believe I have clearly outlined how the motivational structures for these actions are defined by an actor’s cultural repertoire and identity content, both of which are exclusively informed by the social fields through which an interactor travels and with which he or she engages. There is no solid evidence of a direct connection between Manson and Mr. Murdoch, but I strongly believe that I’ve made my overarching point that indirect connections and consequent individual influence by way of social networks can be strongly inferred. As an example of overlapping social fields in this case, FOX provided Interscope with movie options through major Hollywood studios.

Mr. Murdoch’s goal was to establish a global monopoly on multimedia sources and outlets. Throughout the first decades of the millennium, it’s not surprising that he faced competition from other powerful corporate actors. What’s more, Mr. Murdoch’s realization of his vision of a monopoly over multimedia was disrupted by the advent and momentum of social media, particularly Twitter. Thus, it is not a stretch to see how Elon Musk‘s bid for Twitter would position him as an adversary for Mr. Murdoch. Interestingly, prior to this bid, in 2017-2020, James Murdoch, Rupert’s son, served on the board of directors for Tesla and was considered the “favorite” to replace Elon as the chair of the board.



I believe that I’ve adequately illustrated a rough sketch of Mr. Murdoch’s social network with respect to the purpose of the current investigation. Thus, I let out the guerilla scientist in me to interpret the results of my broad content analyses of social fields and identities while also cleaving through the seemingly ubiquitous Leviathan-like bramble that is online information to investigate related persons, entities, and movements. Consequently, I turn to Cluster Tree 4 – fig. 17 because of the surprising introduction of the word, “Trump”. When I first discovered this I was sure to exclude variations in verbiage (i.e., “Trumps”, “Trumped). The branching of thematic dissimilarity raises questions. If you could please take notice, dear friends, that the thematic (dis)similarity of the occurrences of words branches into “charging”, “investigation”, “courts”, “alleging”, “victims”, “epstein”, and “girls”. Also, please take note that “weinstein” is the same color code as “Trump”. What this indicates is thematic similarity. However, they are separated by branches which indicates that the frequency of sentiment or theme with respect to the frequency of particular words makes them dissimilar. What this means, in lay terms, is that a separate theme arises in the data with respect to “weinstein” that differs significantly enough from the other thematic elements of the same color. You’ll notice, dear reader, that a cluster of thematically similar words are attached to “weinstein” distinctly from the “trump”/”james” branch: “womens”, “accusing”, “harassment”, “assaults”, “abusive”, “sexually”, and “records”. This raises a lot of questions as to why these are distinct clusters. I offer some possibilities based on my data.

First, my faithful friend, after digesting my illustration of the overlapping social fields, their constituent interactors, and those interactors’ exchanges, it cannot possibly be a stretch to establish that there are connections through Stephen Feinberg. I must ask that you keep in mind that Mr. Feinberg is the CEO of Cerberus Capital, which is partly funded through Knight global, the Kavanaugh family holding firm. This firm funds the Madison Group, who lobby for Trump. What’s more, he was part of Trump’s Intelligence Board: A position of significant power. This could explain the thematic splits. Passing these data through my theoretical lens, it isn’t a stretch to imagine that in order for Jeffrey Epstein and Ghislaine Maxwell to have been able to carry out their heinous business endeavors, they would have required connections with the highest level intelligence and security communities. Through processes of high-level political social intelligence facilitation and the deflection of public consciousness through the ideological interpellation of the female victim identity by way of the #MeToo movement, elite groups and individuals can exercise what is perhaps the most loathsome form of biopower: the exchange of life itself. Viewing these possibilities through my theoretical lens informs my next steps. I discuss these connections in greater detail in a later section. First, I must continue to flesh out the other interactors and entities connected to the current investigation. I believe it is best to now discuss Mr. Feinberg.

Stephen Feinberg

Mr. Feinberg is a private equity executive who “pumped over $3.2 million into pro-Trump groups since 2016” through the Madison Group alongside Coinbase. His firm, Cerberus Capital also oversees Tier 1, a military group that trained the squad who killed Mohammed bin Salman.



I’ve provided the appropriate social equations to perform, my faithful readers. Similar to how I teased out connections with Mr. Epstein, I performed the same process with Mr. Feinberg. I added any documents I may have excluded as well as some new data that I hadn’t acquired previously. This data set (n=284) can be downloaded below.

I will return to discussions of Mr. Feinberg in later sections of this work but for now I change directions to focus on Mr. Epstein. Again, dearest reader, I ensure you that this choice was made based off data analysis and sound theory.

Jeffrey Epstein

If you aren’t already aware of the situation surrounding Mr. Epstein and his partner, Ghislaine Maxwell, then you can find out more on my internal page, on this Wikipedia page, or some other source of your own choosing. My report focuses on his connections with the Depp v Heard trial and the actors involved. But for the sake of posterity, a brief summary would be appropriate. Mr. Epstein and his wife, Ghislaine Maxwell, are the first of those child/sex traffickers who have been identified and prosecuted. Human Trafficking is, without question, the worst of human evils.

I turn now to analyses of my newly refined dataset (n=284). Again, I present to you the visual representations of my data. The first is a frequency table (fig. 22), followed by a cluster graph (fig. 23), a circle graph displaying strong similarity (p>0.05 and p<1.0 – fig. 24), a circle graph illustrating weak similarity (p>0.0 but p<0.5), another circle graph for weak dissimilarity (p<0.0 and p>-0.1), and the most surprising of all graphs I’ve produced, a circle graph illustrating moderately weak dissimilarity (p<-0.01).


fig. 22 – Frequency Table
Fig. 23 – Cluster Tree of Thematic (Dis)Similarity
Fig. 24 – Strong Thematic Similarity – p>0.5 but p<1.0 – 30 Word Count
Fig. 24 – Weak Thematic Similarity – p>0.0 but p<0.5 – 30 Word Count
Fig. 25 – Weak Thematic Dissimilarity – p<0.0 but p>-0.1 – 30 Word Count
Fig. 26 – Moderate Thematic Dissimilarity – p<0.1 – 30 Word Count

Looking at the cluster tree raises the question, “Why does ‘Trump’ define thematic dissimilarity in this case?” Perhaps because of his connections with Stephen Feinberg. However, before we jump to conclusions, let’s take a closer look.

Mr. Epstein has been involved in covert operations for a long time; if we define covert as purposefully hidden from view. How social fields overlap, merge, and produce subjectivities can be expertly understood through a rigorous interrogation of the case of Jeffrey Epstein and his involvement with the Murdoch Family and his connections to the Depp case.



Remaining true to my data and theory, I must ask again about the thematic branches illustrated in the cluster tree (fig. 23) and the ways in which these branches are distinct in terms of the actors involved. This requires an intimate examination of those actors and the fields through which they travel, the other interactors with which they exchange, the entities scaffolding these milieus, and the competing concepts constituting an episteme. With respect to Mr. Epstein, he has openly admitted to organizing and/or supporting clandestine pseudo-movements as a front for violations of the law, such as “Times Up”. This organization was presented to the public as a movement to raise awareness and capital for victims of sexual harassment. Meanwhile, the “CEO Tina Tchen and Time’s Up Legal Defense Fund chairwoman Roberta Kaplan both resigned over their roles in the Cuomo scandal“. If you’ll remember, dear reader, Kaplan was Amber Heard‘s original attorney for the US trial.

“Kaplan resigned after the investigation found she had been involved in efforts to try and discredit Cuomo’s first public accuser, Lindsey Boylan.

Just days after Cuomo resigned, Tchen also stepped down as CEO after text messages revealed she had initially discouraged Time’s Up leaders from making any public comment about Boylan’s allegations.”



The administrators of a social movement designed to raise funds and awareness for victims of sexual assault were active participants in covering up a series of sexual assault scandals. It’s no surprise that one of these actors, Roberta Kaplan, is intimately tied to the Depp v Heard case. What’s more, Jeffrey Epstein openly admitted to his support for the group. A man found guilty of sexual and human trafficking expressed his support for a group who actively covered up sexual assault scandals. I hope, dear reader, that the architecture has been rendered more clear. To continue fleshing it out, I must turn to an analysis of how and why “amber” shows moderate dissimilarity to “trump”. I turn my attention in this direction for several reasons. First, the cluster tree (fig. 23) strongly suggests that something invokes the fracturing of thematic similarity of the frequencies of the occurrences of words surrounding “trump” as it relates to items of particular interest in this case, including “sexually”, “abusive”, “epstein”, and so forth. Second, it’s of particular importance because of the previous discovery of the involvement of Cerberus Capital and it’s CEO Stephen Feinberg‘s involvement with Trump’s Intelligence Board and lobbying group. And, third, it’s of remarkable utility to discover here that the branching of thematic relevance that leads from “trump” to “epstein” is related to a weak tie between “trump” and Amber Heard.

For a better grasp on how these elements tie together, I must again assert that Pierre Bourdieu’s theory of social fields serves great utility. For example, below are pictures from the Illy “Grand Classics” event at the Core Club NYC in 2013.


Harvey Weinstein & Coralie Charriol Pau – 2013
Kelly Rutherford & Ghislaine Maxwell – 2013

Amber Heard was on the rise during this time and had been roving through these kinds of social fields to accrue more and more social, cultural, and symbolic capital. Within and across these groups, Amber was exchanging identity content and definitions of behaviors with these other interactors. She was gaining increasingly broader access to various resources while also learning the norms and values required for greater mobility through and across these social fields as well as greater access to various forms of capital. Shortly before this time, while Amber was breaking into the public limelight in 2009, Maxim publisher Alpha Group experienced the loss of one of its two major investors, the Quadrangle Group. Left as majority owner of the company? Cerberus Capital.



That’s right. Cerberus. The company that was the investment destination for a number of the actors I’ve mentioned already. The relevance of this can be clearly illustrated by examining how Maxim can influence the public narrative surrounding how women are portrayed. Amber performed a photo shoot for the cover of Maxim in 2008.



The relevance can also be explained by the now clear connection from Ms. Heard through Maxim to it’s majority owner Cerberus Capital to Cerberus CEO Stephen Feinberg who would eventually serve on Trump’s Intelligence board. This Capital Holding Firm – that is tied to the producers and executives addressed in this investigation – owned the magazine that gave Amber one of her biggest breaks into the market. Less than one year after this photoshoot, a major investor with Cerberus Capital, Ryan Kavanaugh, cast Ms. Heard in Zombieland. It doesn’t take much imagination to recognize how these different social fields took shape, how Ms. Heard traveled through them, the kinds of social exchanges that were made, or the ways in which these connections would lead to the weaponization of false allegations to persecute innocent men. Considering the Freedom Group, subsidiary of Cerberus Capital, were literally constructing weapons around this time – some of the first AR-15s – ought to further clarify the kinds of cultural repertoires, opportunity structures, and identity contents made available. This begins to scratch the surface of explaining the weak tie between “heard” and “trump” as illustrated in fig. 26 that is most likely a major explanatory factor for how thematic branches differ based on the frequency of the word “trump” in fig. 23. Remember, faithful reader, the strength of weak ties.

I want to be clear. This does not mean that I am suggesting that Amber was connected directly to Trump. Whether or not she ever met the man isn’t the matter at hand in this analysis. What this weak connection suggests is that there were overlapping social fields. This revelation emerging from the thematic analysis of the content I’ve collected would suggest that someone is connected to Amber in such a way that their social fields overlap and that someone‘s social fields overlap with Trump. Although arguable if only considered a theoretical stretch, the frank evidence I’ve provided strongly supports this conjecture. Sound theory coupled with naked evidence strongly asserts that this connection can be explained by Amber’s indirect involvement with Maxim, Cerberus Capital, and Stephen Feinberg. This is important to reveal because of the relationship to Amber’s career as I’ve outlined above. Drawing from my theoretical frame, particularly differential association and differential opportunity theories – both of which are extensions of social identity and identity theories more generally – I must assert that we examine this series of overlapping social fields in terms of the ways in which these fields impose forms of conditioning and call forth certain subjectivities.

My assertion bares extreme relevance with respect to the interface between Jeffrey Epstein, Ghislaine Maxwell, Human Trafficking, and their relationships with how the intersections between Radical Feminism and State Intelligence Communities made capable the production of certain kinds of subjectivities. I will break this down throughout my analysis of Stephen Feinberg that follows, faithful reader.

Stephen Feinberg – cont’d

Mr. Feinberg is the co-founder of Cerberus Capital est. 1992, has been CEO of the firm since 2012, and has served as the special advisor to Trump’s Intelligence Board from 2018-2021. I focus primarily on his connection to this case and the broader correlated precipitants and ramifications. If you want to learn more about Mr. Feinberg, you can turn to my internal page or Wikipedia. These biographical elements are important to my analysis and I use them throughout.

I needn’t assert again, dearest reader, my belief in how social learning is foundational to understanding human behavior. The mentor process is a crystallized example of this. Mr. Feinberg was mentored by “junk bond king” Michael Milken.



The significance of this applies to our understanding of every hedge-fund billionaire that I’ve identified as connected to this case. What I mean by this is that these social fields clearly overlap and thus the cultural repertoires of these interactors could be expected to come into some modicum of alignment. As a further example of how this applies via weak ties, the fact that Cerberus Capital owned Maxim at the time of Amber Heard‘s photoshoot for the magazine is no coincidence to overlook. Although a weak tie, Amber’s connection to Mr. Feinberg can be established. As I’ve established, less than a year later, Amber was featured in Zombieland, produced by Ryan Kavanaugh. It’s also important to note that this wasn’t the only time that Cerberus and Mr. Kavanaugh performed direct business with one another. Cerberus also owns Spyglass Entertainment who have been investors into a number of films associated with Mr. Kavanaugh and Relativity Media. As a film financier and hedge-fund investor, Mr. Kavanaugh performed business with Cerberus through studios and the film industry as well as through various hedge-fund investments as I’ve outlined in other sections of this work. Also in previous sections I’ve already successfully established Mr. Kavanaugh’s friendship with Mr. Weinstein and thus, by proxy, to Mr. Murdoch. I’m certain, dear reader, that you are also aware of the connection that these men held to Jeffrey Epstein and Ghislaine Maxwell.



The two men were clearly involved intimately within concentrated social fields of shared values. The importance of recognizing this becomes even more apparent when we introduce Mr. Feinberg into the field. As we are all aware, Jeffrey Epstein has been found guilty of sex-trafficking children. As I’ve successfully established in previous sections, for him to have been capable of these actions, he would have needed high-level Intelligence and Security connections. First, there have been numerous reports of Epstein using a plane with an FAA tail number registered to Cerberus Capital. This is one blog post of many.



I’ve also already established in previous sections of this work how the Intelligence Community was connected with both Epstein and Feinberg during this time. This is important because it was during this time that Cerberus were also involved in lobbying for Trump via the Madison Group, alongside the FOX corporation and Coinbase, the latter of which were the major investor into Ryan Kavanaugh‘s crypto-currency Proxicoin.



It was reported that Trump was tapping Feinberg to take charge as an auditor of the Intelligence Community to help identify and redress suspected Intelligence leaks.



The corporate team at Dyncorp, a military contractor owned by Cerberus Capital, were clients of the same organizational consultant as Kavanaugh‘s other media company Proxima. This consultant, Bart Allen Barry, also worked with the Republic of North Korea and he Sultanate of Oman.



Furthermore, private military contractor Dyncorp, a subsidiary of Cerberus, have also been suspected of trafficking women and children in Bosnia and Herzogovina.



I’m certain, dear reader, that I’ve cast these actors and entities into stark relief for your observance. In order to better refine my illustration, I turn to my research methodology and theoretical framework. Because of the arising salience of the name, Stephen Feinberg, it is necessary to perform another round of data collection that includes Mr. Feinberg, Dyncorp, and another subsidiary of Cerberus Capital, the Freedom Group.

Data Collection 3

Updated on July 21, 2022

Following the same methodology informed by the same sound theory, I collected another group of articles to include in my data sets; articles which included the names “Stephen Feinberg”, “Dyncorp”, and “Freedom Group” (n=368). Again, these data were refined by way of vetting based on the same factors I’ve outlined previously. You can download this data set below.

Analyses and Interpretation of Results

Having collected and reorganized my sources of data, I was compelled to begin by performing a broad thematic analysis to get a better feel for the overall sentiments, themes, and the ways in which they’re interrelated. Therefore, I present to you, dear reader, four infographics that explain different kinds of thematicism and/or (dis)similarity across the top 55 results in the dataset. I strongly suggest you take a good look at them

The first is a cluster tree organized by thematic code (fig. 27) and the second is a circle graph of strong similarity (fig. 28 – p>0.7 and p<1.0), the third is a circle graph of moderate similarity (fig. 29 – p>0.3 and p<0.7), and the fourth is a circle graph of weak dissimilarity (fig. 30 – p<0). There were no results with a p-value lower than -0.1. This is understandable since the overall sentimental current of each these articles could be expected to align quite closely with one another.

As the images are too large to be properly displayed on this web page, they can be downloaded here:

Cluster Tree of Thematic Similarity

Items clustered by thematic similarity Circle Graph – Strong Similarity

Items clustered by thematic similarity Circle Graph – Moderate Similarity

Items clustered by thematic similarity Circle Graph – Weak Dissimilarity

These analyses and graphics inform my decisions with respect to narrowing the scope of my thematic coding and which words to include or exclude from my various cluster analyses that were to follow. Since I am primarily interested in how other powerful actors are associated with this case – particularly Stephen Feinberg – I refined my search criteria appropriately. I present below a frequency table of word occurrences (fig. 31), a cluster tree of thematic similarity (fig. 32), a circle graph of strong similarity (fig. 33 – p>0.7 but p<1.0), a circle graph of moderate similarity (fig. 34 – p>0.3 but p<0.7), a circle graph of weak dissimilarity (fig. 35 – p<0.0 but >0.1), and a circle graph of moderately weak dissimilarity (fig. 36 – p<0.1). All of these were performed with a 55 word count.


fig. 31 – Table of Occurrences of Word Frequencies

fig. 32 – Cluster Tree of Thematic Similarity

fig. 33 – Circle Graph of Strong Thematic Similarity – p>0.7 but p<1.0 – 55 Word Count

fig. 34 – Circle Graph of Moderately Strong Thematic Similarity – p>0.3 but p<0.7 – 55 Word Count

fig. 35 – Circle Graph of Weak Thematic Dissimilarity – p<0.0 but p>-0.1 – 55 Word Count
fig. 36 – Circle Graph of Moderately Weak Thematic Dissimilarity – p<-0.1 – 55 Word Count

As you can see from the cluster tree (fig. 32), “Weinstein”, “Murdoch”, “Maxwell”, “Epstein”, and “Andrew” are are closely related in tone, sentiment, and occurrence, but break off into their own distinct sets of themes. I will break this down in a further section that follows. First, I want to address the elephant in the room. That is, the clear depiction in fig. 36 of the weak ties between Mr. Feinberg, Amber, and Johnny. You will notice that Mr. Feinberg also has weak ties to “Equity”. This ought to illustrate what I have meant all along about the strength of weak ties. To make it clear, there is no way that Mr. Feinberg, the CEO of a Capital Investment firm, is distinct from “equity”. He must, by the very nature of his position, be mentioned in association with the term. Instead, we can think of the two as clearly associated but distinct in sentimental tone; or that they are embedded within different emotional contexts.

The strength of weak ties within the context of Dynamic Social Network Theory is a very important consideration with respect to Mr. Feinberg’s clear dissimilar connection to both Johnny and Amber. As I’ve stated previously, at an interpersonal level these weak ties are most often the vectors for social contagion between two distinct populations. In other words, it is through associates with less intensely personal relationships that social psychological phenomena are most easily passed between two groups that would not normally socialize with one another. The social norms or psychological contents of members from one group are transmitted to the other and are thereafter subject to potential diffusion among the new population. This proposition has been rigorously tested and has yet to be falsified. In fact, it is one of the foundational building blocks of most bodies of work that deal with organizational or group psychology.

Also for consideration on the interpersonal level, weak ties have proven to be the primary means through which distinct populations exchange or distribute desirable resources, whether that be financial, social, symbolic, or cultural capital. Perhaps more importantly, weak ties also tend to be the vectors through which actors transmit role-perspectives, emotional values, and personal motivations to another distinct group. You cannot deny, dear reader, that “the personal experience of individuals is closely bound up with larger-scale aspects of social structure, well beyond the purview or control of particular individuals” (Granovetter, 1973:pp.1377), or, in other words, that weak ties play a pivotal role in an individual’s opportunity for social and economic mobility. Granovetter (1974) puts it in this way: that there is a “structural tendency for those to whom one is only weakly tied to have better access to job information one does not already have. Acquaintances, as compared to close friends, are more prone to move in different circles than oneself. Those to whom one is closest are likely to have the greatest overlap in contact with those one already knows, so that the information to which they are privy is likely to be much the same as that which one already has” (pp.52-53). In Hollywood celebrity culture, where many of the individuals are hungry for status, fame, and capital, it is through these weak ties that one can make his or her “break”. As I outlined in previous sections of these analyses and in the section on Amber Heard, this is exactly what she did. But, as I hope that you are now seeing, these “breaks” do not occur in a vacuum, but, rather, within and across social fields wherein other interactors play a significant role in the outcome.

As I established in previous sections of this work, 2008-2009 was one of the most important points in the trajectory of Ms. Heard’s career. This was when she had her “break” into the public imagination. Her cover shoot for Maxim magazine at the time played a huge role in this “break”. At the time, Maxim was owned by Cerberus Capital, the founder and CEO for which is Stephen Feinberg. What’s more, Cerberus Capital was an investment destination for both Harvey Weinstein and Ryan Kavanaugh. It must go without saying that two major film producers would hardly invest millions of dollars into a firm without having met with it’s board and Chairman. Less than one year after her Maxim cover shoot, Ms. Heard was featured in Zombieland, which was produced by Mr. Kavanaugh. Not only did Mr. Kavanaugh direct a number of his economic interests towards Cerberus Capital, his film production company also hired former Cerberus staff.



What’s more, Mr. Kavanaugh began a cryptocurrency called “Proxicoin”, which is a securities token built on the Ethereum platform. This was made possible through a $100-million loan from fellow crypto guru, Coinbase, who just so happen to support political lobbyists, the Madison Group, alongside FOX and Cerberus Capital. At this point, dear reader, we are no longer discussing weak ties. Instead, we can easily gain purchase on the applicability of ideologically-based homophily to these over-lapping social fields. In simpler terms, this concept describes how people are more likely to socialize with others who share their ideology, or, in other words, with others who share very similar identity content, cultural repertoires, political beliefs, socioeconomic status, and so forth. This explains how the sources for the patterns of thought and behavior for members of such groups most often align with one another. It is well know that Mr. Feinberg is a highly secretive man and so there is very little public information that ties Mr. Feinberg to Mr. Kavanaugh or Mr. Weinstein besides some financial records and CH 11s. However, it is not a stretch to assume they were closely associated. Millions of dollars in investments tend to do that.

Another thing that is important to consider at this stage that strengthens my interpretation is how ideologically-based homophily is affected by political avoidance norms and perceived group position. Political avoidance refers to the ways in which individuals are motivated to disassociate with others who do not share the same political beliefs or standards, whereas perceived group position refers to the ways in which a group perceives themselves in relation to other groups. These two interrelated factors have been shown to moderate the strength of ideologically-based homophily between individuals and, more importantly, between groups. This matters in terms of how changes in access to and distribution of various capitals may vary over time for not just particular members of a certain group but overall for the perceptions that members have of the group to which they belong; especially in relation to perceptions of the same in some competing group. This is what is known as perceived group threat, that is, the shared perception that the access and distribution of various capitals for the group has been compromised or is under threat because of the collective actions of some other group. This perceived group competition has a significant effect on the motivational structures of the members of any particular group. This central component of group/organizational social psychology is very much informed by understandings of interpersonal dynamics; and within criminological theoretical frames in particular, Differential Association, Identification, and Opportunity theories play a critical role. I’d like to use the example of Mr. Kavanaugh and Mr. Weinstein to explain how all of these theories and their conceptual components can dovetail together into a cogent and cohesive perspective of the Depp case and related parties.

Feinberg, Epstein, Kavanaugh, and Weinstein

The close relationship between Mr. Kavanaugh and Mr. Weinstein has already been established in previous sections of this work. It is their relationships with Mr. Feinberg that I seek to better establish for you, dear reader, by utilizing the sound theory I’ve laid out for you. Some members of the public, including you, faithful friend, might know this kind of work as “profiling”. This term can work but can also carry a pejorative meaning for some people. Nonetheless, there is great value to using tried-and-tested tools to illustrate a model of the character of individuals as this can provide insightful possibilities for explaining their social position relative to others, their motivations for actions within these relationships, the impact of these relationships on interactors, and the general shared cultural repertoires of a particular group. In this vein, I believe it’s important to recognize that the year that Mr. Feinberg became a “special advisor” to Trump’s Intelligence board – what could basically be described as an auditor – Deutsche Bank, a major donor to Trump, was investigated for money laundering. Who held a percentage ownership of Deutsche Bank at the time? Cerberus Capital.



The relevance of this relates directly to Deutsche Bank’s financial dealings with Jeffrey Epstein.



Alongside their ties with the above scandal, Mr. Feinberg and his powerhouse firm also own DynCorp International, an American private military contractor who trains and deploys soldiers, trades arms, and also allegedly trafficks human beings in Kuwait, Bosnia, and Herzegovina, among myriad other military theaters.



For further consideration, dear reader, I must bring your attention to how, from 2015-2018, Cerberus Capital were in financial hot water – just like Weinstein’s and Kavanaugh’s film businesses.



As we can see from their highly agile investment habits, these powerful actors are able to pivot on a dime depending on the state of the current markets within which they operate. Whether it’s pivoting from private capital to arms-dealership, like Mr. Feinberg; or from film equity leveraging to boxing broadcasts with Snoop Dogg, like Mr. Kavanaugh; through the lenses of Differential Association, Identification, and Opportunity theories, it’s not difficult to recognize the patterns in the fiscal habits of these interactors nor is it difficult to recognize how their intimate exchanges must include definitions for the most favorable outcomes in terms of capital accumulation, that is, definitions for behaviors favorable to capital accumulation regardless of violations of the law; as well as those kinds of justificatory processes for dealing with any justice systems.

Within and across nodes of this dynamic social network floated none other than Amber Heard, the newly established figurehead for the supplantation of the highly profitable victim-identity in place of womanhood. The internally inconsistent logics of Radical Feminism – which claims sole-authority over defining victimhood/oppression and the same authority over arbitrarily delineating between oppressor and oppressed – alongside the #MeToo movement – which enforces the division between men and women at the risk of violence while also claiming the sole authority to determine membership to either the ingroup or outgroup – the stage was set for the willful atomization of any social collective that may choose to stand against this social force while also galvanizing an emergent industry of prosecuting wealthy and famous men for profit. Of course, this has been built off the tried-and-tested entrepreneurial of creating victims for profit through manifest violence. I mean, what else is war other than creating victims for profit? Yes, some wars are necessary, but from a corporate and political perspective, they are nothing more than business-as-usual.

Having successfully established how these actors, the Intelligence community, and general social contagion gathered into the maelstrom that almost carried Captain Jack to his demise, I believe it’s incredibly important to turn my attention to Google’s connections with the Intelligence community and thus Ken Dauber, husband to Mrs. Heard’s Handler, Michele Dauber.

Michele Dauber – The Handler

July 30, 2022

Michele Landis Dauber is a law professor and sociologist employed at Stanford University since 2001 and received tenure in 2007. Michele’s husband, Ken Dauber, is a software engineer at Google. He was Google’s 9th employee hire, which would indicate that he has been highly influential in their development. I discuss Ken in other sections of this work and focus on Michele in this section. If you would like further personal or professional information on Michele, then you can find that on my internal page or on Wikipedia. In this section I discuss her connections to and involvement with the Depp v Heard case and surrounding interactors.

I would like to begin by examining Michele’s involvement in People v Turner; a high-profile case involving sexual assault allegations by Chanel Miller that were leveled against Brock Turner. On March 30, 2016, Brock was convicted by jury trial of three counts of felony sexual assault. “On June 2, 2016, Santa Clara County Superior Court Judge Aaron Persky sentenced Turner to six months in jail followed by three years of probation. Additionally, Turner was obliged to register as a sex offender for life and to complete a rehabilitation program for sex offenders”. Michele was friends with Chanel Miller’s family and involved in the production and 2016 dissemination of Chanel’s victim impact speech. Consequently, Michele expressed great disgust over what she deemed as an insufferably light sentence for Brock. She subsequently lobbied for the recall of Judge Persky, which succeeded as he was recalled on June 5, 2018.

Although there are many suspicious events surrounding Dauber’s involvement in Judge Persky’s recall, I do not address that here. If you would like more information about this case or Dauber more generally, you can find that on my internal page or the Wikipedia page. In order to take a detailed look at Dauber’s involvement in the Depp case, I decided to perform another content analysis and thus it was required that I perform a separate data collection. Using the same aforementioned methods, I collected as many related online articles as possible until I reached a suitable level of data saturation while also observing that my sample was of adequate enough size that it would not affect the validity of my analyses (n=108). In the name of transparency and attempted replication, you can find these data here:

With these data I once again performed the same thematic cluster analyses as I did before with the previous data sets. However, since I am dealing with one individual in particular, I decided to examine a larger number of the words in the content and consequently expanded my analyses to include the 50 most frequently occurring words. For your viewing pleasure and dramatic effect, I first present a WordCloud (fig. 37 – WordCloud – 50 Word Count). Below that is a word frequency table (fig. 38 – Word Frequency Table – 50 Word Count). Following that I present a cluster tree that illustrates word occurrences by clustered thematic similarity (fig. 39 – Cluster Tree – 50 Word Count). Because I wanted to perform as fine-grained analyses as possible, I generated (dis)similarity word graphs for each decimal place of p-values. There were no p-values below -0.02. Thus, I present 10 similarity word graphs (between p>0 and p=1) and 2 dissimilarity word graphs (between p<0 and p=-0.2).

fig. 37 – WordCloud – 50 Word Count
fig. 38 – Word Frequency Table – 50 Word Count
fig. 39 – Cluster Tree – 50 Word Count
fig. 40 – Similarity Circle Graph – between p=0.9 and p=1
fig. 41 – Similarity Circle Graph – between p=0.8 and p=0.9
fig. 42 – Similarity Circle Graph – between p=0.7 and p=0.8
fig. 43 – Similarity Circle Graph – between p=0.6 and p=0.7
fig. 44 – Similarity Circle Graph – between p=0.5 and p=0.6
fig. 45 – Similarity Circle Graph – between p=0.4 and p=0.5
fig. 46 – Similarity Circle Graph – between p=0.3 and p=0.4
fig. 47 – Similarity Circle Graph – between p=0.2 and p=0.3
fig. 48 – Similarity Circle Graph – between p=0.1 and p=0.2
fig. 49 – Similarity Circle Graph – between p=0.0 and p=0.1
fig. 50 – Dissimilarity Circle Graph – between p=0.0 and p=-0.1
fig. 51 – Dissimilarity Circle Graph – between p=-0.1 and p=-0.2

Michele Dauber – 2nd Data Collection

August 5, 2022

I will return to interpreting the results above throughout my report. However, because I found the results somewhat limited, I decided to collect more data. I broadened my search criteria to included Ken Dauber, Michele’s husband, as well as other actors involved within this matrix (n=152). These new data, along with the same data from above, can be downloaded below.

With this newly amalgamated data set I performed the same cluster analyses as before. In this case, however, I chose to include more words; 100. My reasoning for this is that I am seeking to explore the broader landscape of persons, events, entities, and so forth, associated with Dauber. I chose a different approach because the previous data sets already included a variety of search terms that allowed collecting data that included other associated entities or persons. In this case, because I am dealing with only a few individuals in my searches, it was important to explore the data in greater depth and detail. Consequently, by including a broader number of words and themes, circle graphs of (dis)similarity are nearly impossible to interpret because the webs of relationships are simply too complex to present any graphic utility. The dendogram, or cluster tree of these data, however, is very very telling. Very telling indeed. I present this cluster tree of thematic similarity below (fig. 52 – Cluster Tree – 100 words).

fig. 52 – Cluster Tree – 100 words

Carefully interpreting the results of these cluster analyses took some time. I was faced with rerunning the analyses a number of times, removing certain words, re-adding words I may have previously removed, and so forth. This process isn’t the same as tampering with the data or analyses at all. Instead, it’s a process by which a researcher can tease out particular connections or similarities without affecting the data itself. Consequently, the above dendogram tells a very complex and interesting story when combined with further investigative journalism into the timelines, stories, and events to which the “branches” refer.

There are a number of important resources that address Dauber’s involvement in the People v Turner and discuss important details about the case. One central resource is Save Our Sons, who examine the police reports, court documents, and public records related to the case. The summation of their findings – which raise some very serious questions about procedural fairness – can be found in the document, “Seven Big Lies in the Brock Turner Case; Plagiarism at Stanford”.

As I previously outlined, Santa Clara Superior Court Judge Aaron Persky presided over the People v Turner, which concluded in June of 2016 with Judge Persky sentencing Brock Turner to 6 months in prison for the sexual assault of Chanel Miller. Although this was the sentence recommended by the Santa Clara Probation Department, Dauber became extremely vocal about how this sentence was far too lenient. She then proceeded to engage in an activist campaign to have Judge Persky recalled from his position and she succeeded; the first time a judge was removed in 80 years. Before I delve any further into Dauber’s debauchery in this particular instance, I ask you to observe the cluster tree above (fig. 52) to better understand the justifiable inferences I will make for you, dear reader.

As you may well already be aware, 2016 was the year that Hilary Clinton was running for President against Donald Trump. The election took place in November, conveniently preceded by the Brock Turner conviction and accompanied by Dauber’s consequent activism. Below, you can see the outcome of the polls for Santa Clara, California, where Brock was found guilty.

As you can see, Hilary Clinton swept the polls in Santa Clara. In the cluster tree above (fig. 52) you can see the teal, aqua, and purple thematic clusters that coincide with the win for Democrats in Santa Clara. This is no coincidence. Prior to the Brock Turner case, Dauber had been involved to a greater or lesser degree in three other similar cases that would have been able to provide similar weight to her “Girl Cult” fanaticism: 1. Leah Francis, a victim of sexual assault who held rallies at Stanford in an attempt to have her perpetrator expelled; 2. Elise Clougherty, who claimed that a Stanford alum, Joe Lonsdale, had sexually assaulted her during a year long relationship, and 3. “Mattress Girl” (the “Carry That Weight” Demonstration) – a performance art thesis by Emma Sulkowicz on Columbia campus whereby Emma carried a 50 pound dorm mattress on her back to represent the weight that sexual assault victims must carry on a daily basis.

Not only was Dauber involved with the above phenomena but she was also friends with the family of Chanel Miller, the victim in the Brock Turner case. She authored the “Emily Doe” letter – Chanel’s victim impact statement – and disseminated it prior to the outcome of the trial; recipients of which included the producers of the 2015 film, “the Hunting Ground”, which highlighted the “epidemic” of sexual assault on US college campuses. This dissemination occurred prior to Brock Turner hearing the impact statement during his 2016 sentencing. What’s more, not only did Dauber fight to have Persky recalled, she also publicly called for people to commit violence against Brock. Consequently, a terrifying rally of anarchists carrying AR-15s gathered at Brock’s family home.

I won’t get into the nitty gritty of the Brock Turner case. I’ll leave that for you to research further. My collaborator and colleague, @LetsHearTheTru, wrote a piece on it that you can find here. Seeing as my cluster analysis clearly aligns with this series of events in manifest reality, dear reader, I must turn your attention to other research that will fully inform the other important branches of the cluster tree (fig. 52). The Brock Turner case is just one aspect of Dauber’s career and activism that is worthy of our attention. Prior to the abovementioned events, Dauber met her husband Ken at Northwestern University. While in attendance there, Dauber also met and became close with future rabid advocate in Education for the Office of Civil Rights (OCR), Russlyn Ali. While an acting member of the OCR, Russlyn hired Ken Dauber – the 9th Google employee and an early developer for Netflix – as a professional consultant. It was during this time, in and around 2008-2009, that Michele Dauber wrote the infamous “Dear Colleague” letter: an OCR Title IX proclamation that was purportedly designed to more effectively and forcefully address incidents of sexual violence among college faculty and students alike. It was Dauber’s good friend, Russlyn Ali, active OCR activist and officer, that signed this letter into being.

As I have more than clearly illustrated, Michele Dauber had ties to the DNC and her activism served great utility for the party and their candidate, Hilary Clinton. The relevance of this cannot be overstated because Dauber and other radical feminists and sexual-assault-identity entrepreneurs like her have used political lobbying for decades to raise millions of dollars to fill various corporate and political coffers. For example, Dauber’s “Enough is Enough” voter project – which sought to “make violence against women a voting issue” – has raised hundreds of thousands of dollars. Yet, I ask you, dear reader, for what? I’d like to address answering this question, but first I provide to you some receipts on Dauber’s “movement”. Below you will find two locations that track the capital flowing through this organization as well as a link to their website. I ask that you pay close attention to their “about us” “impact statements” before I dissect all this using sound social psychological theory and the results from my data analyses.

I hope that you were able to recognize, dear reader, how the “impact statements” for the organization are grouping separate civil rights issues and unverified character judgments under one sweepingly generalized umbrella concept of “violence against women”; abortion laws, sexual assault allegations, and so forth. I hope that you were also able to identify their strategic choice of rhetoric; “attack”, “victory”, “anti-survivor”, and so forth. The one statement alone, “Perdue…wanted to put guns in the hands of domestic abusers”, is such a ridiculously obvious reframing of the facts that its laughable. Anyways, onto the dissection.

As promised, dear reader, I return to my sound theoretical framework. In this case, the corpora of literature on Social Identity Theory & Identity Politics. These interrelated theories enable us a clearer grasp of how Radical Feminists like Dauber have been able to mobilize such broad swathes of the public. As previously outlined in my theory section, a social identity can be “understood in terms of how members of opposing groups tend to behave towards each other as a function of their respective group memberships rather than because of individual characteristics or personal relationships”. Alongside this, groups and individuals can politicize aspects or shared status-characteristics of these social identities, that is, inspire collective action towards a political objective by making some part of a social identity into a value that could be shared by a larger group. Michele Dauber and her debaucherous tricksters have done just that by conflating womanhood with victimhood.

The crystallization of the “women-as-victims” social identity has been a collaborative effort (hence the “collective action” framework). Tracing Dauber’s connections back in time from “Enough is Enough” reveals a lineage of equally corrupt radical feminists who share the same political objectives. The “Enough is Enough Voter Project” rose into its own, ironically, in and around the same time as the Times Up scandal. If you aren’t already aware, dear reader, Times Up is a non-profit designed to capitalize on the rapidly expanding MeToo movement and raise funds for sexual assault survivors. Headed by former Amber Heard Attorney, Roberta Kaplan, and former Chief of Staff to Michele Obama, Tina Tchen, this organization founded the Time’s Up Legal Defense Fund which drew it’s resources from the National Women’s Law Center. When Time’s Up directors were found to have attempted to discredit survivors stepping forward with respect to sexual assault allegations against Andrew Cuomo, Tchen and Kaplan stepped down and the organization shuffled their board members. Dauber was especially vocal against Tchen.

It’s not surprising, then, that Roberta Kaplan, Amber Heard’s former attorney, “mysteriously” withdrew from the Depp case shortly before these events. Whereas the press release stated “logistics” as her reason, Adam Waldman has publicly stated that this purported explanation for her withdrawal is dubious. Amber had been closely tied to Dauber’s “Enough is Enough” Voting Project for years, acting as spokesperson and ambassador.

The crystallization of the “women-as-victim” social identity had reached critical mass around this time and political lobbying funds were at an all time high. If we apply Differential Association and Differential Opportunity theories in tandem, then we can gain greater purchase on this culmination of strategic collective (and, frankly, mostly criminal) action. As the social identity of “women-as-victims” was increasingly popularized and politicized, it’s profitability increased. Those actors who are invested in the identity are more likely to engage in ritualized interactions with others with similar identity content. Through these exchanges, behaviors that are favorable to elevating the social status of that identity are learned, refined, adapted, and, generally, perfected. What’s more, during these exchanges, these actors also negotiate the legality of their increasingly shared political objective. Strategies for circumventing any legal obstacles can be compared against one another and new community regulations developed out of existing repertoires. That is, these actors develop their own rules to navigate societal channels in order to further advance their group’s social position in relation to other groups. New opportunities are made available, specifically to those who share and reinforce this social identity. In this case, the “woman-as-victims” social identity was gaining sacred status whereby never-before-seen opportunities for increased social position and capital accumulation were being made available to those women who would embody that identity. And every victim needs a perpetrator. Thus, the collective would celebrate those women willing and able to facilitate the strategic persecution of innocent men for the accumulation of social and cultural capitals for the social identity defining the group.

These associations – by which actors learn behavior patterns which validate their identity, regardless of whether it violates norms or laws – and the relevant opportunities for action made available to increase social status and accumulate capital – whether financial, cultural, social, and so forth – clearly did not manifest from thin air. Lets take another step backwards in time to examine the precipitating elements and how deeply that Dauber and others were involved. Evan Rachel Wood’s lobbying of congress in 2018 was not arbitrary. It was strategic. Building on Jeanne Shaheen’s 2016 “Victim’s Bill of Rights”, Wood was able to elevate the politicization of the victim identity from a civil rights issue to a matter of Homeland security. The “Sexual Assault Survivors Bill of Rights Act” evolved into the Pheonix Act, which was a similar detriment to due process as the outcome of the “Dear Colleague” movement at Stanford and other post-secondary institutions. Shaheen’s bill was an evolution of Obama’s 2014 “Not Alone” task force, which was designed to work with police and officials to target campuses displaying “rape culture”. It’s clear that at this time there were certain new subcultural or community-level legal and behavioral norms incubating among those who espoused the “women-as-victim” identity. I must be clear, dear reader, that this identity does not present itself as “weak” or “fragile”. Quite the opposite. The embodiment of this particular “victim” identity is founded upon the notion that women are ubiquitously and historically victimized and it’s adherents present as fervent activists that seek to dismantle “patriarchal systems of oppression”, that is, they believe that social structures have been painstakingly crafted over time to purposely disadvantage, exploit, and diminish woman and that their life purpose must be to resist, if not destroy, these systems. The “Dear Colleague” letter, which promulgated Title IX legislation that has unequivocally threatened the lives and well-being of young men on college campuses and beyond, was authored by Michele Dauber, signed by Russlyn Ali, and elevated by the Obama administration.

We now sit with examining the real victims of this dysfunctional collective action designed for the accumulation of social, cultural, and financial capital. Owen Labrie. Brock Turner. Roman Polanski. Marilyn Manson. Johnny Depp. The list is likely endless. Currently, myriad individuals are profiteering off the backs of these persecuted men. The Prout Family. Michele Dauber. Roberta Kaplan. Tina Tchen. Vital Voices. Hillary Clinton. The list goes on. All because of the gradual erasure of due process and the elevation of women’s voices to where their allegations can be considered the equivalent of a judge’s gavel strike. It would be no surprise, then, based on the histories and networks that I have shared with you, dear reader, that numerous inferences are made available. Examining the cluster tree (fig. 51) once again, we can see how nearly every cluster divides into branches based upon certain differing criteria. Inspecting and interpreting this carefully, it becomes readily apparent how “statements” and “opinion” take precedent over process and procedure. This kind of transformation of due process and public opinion cannot occur from simple protests or administrative skirmishes. No. This kind of drastic and detrimental transformation of our social contract can only come about by way of carefully planned social engineering; a collaboration between powerful governmental and corporate actors, academic policy-makers, and stakeholders. Michele Dauber being married to Google’s 9th hire is no coincidence. Google’s imbrication with the US Intelligence community is equally no coincidence in this story. Dauber and “Dear Colleague” have been a coordinated assault on the public by Intelligence and Corporate partnerships designed to divide us while also disguising nefarious and repugnant activities being carried out by these same corporate actors. It is not a stretch to presume that Michele Dauber was instructed – by way of her husband Ken – to groom and elevate Amber Heard to the status of fountainhead of this highly profitable enterprise. As I’ve clearly outlined, academic institutions and the DNC gained more from this than we could properly quantify. Whether Amber was aware of it or not – because she was clearly sucked into the eyes-wide-shut dark-side of this operation – she was a product of all these moving parts and motivated actors. She was their asset, designed to elevate their status and pad their pockets. And Michele Dauber was the architect.

More coming soon…

For now, you can find a field map and and interactive visual module HERE.

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