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Spurious correlation #4,470 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Libertarian Presidential candidate in California and the second variable is Automotive recalls for issues with the Parking Brake.  The chart goes from 1980 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the level of political freedom rhetoric in the state decreased, the molecules in the air became less likely to engage in rebellious behavior. This led to a harmonious alignment of atomic particles within the parking brake systems, effectively reducing the need for recalls. It's as if the ideologies of individual choice and limited government intervention had a direct impact on the mechanical operations of parked vehicles. Who would have thought that the political climate could pump the brakes on automotive malfunctions? Remember, when it comes to liberty and parking brakes, every vote counts!

Model: dalle-3
Prompt: Prompt: Generate an image portraying a lighthearted and harmonious scene in California. Show parked cars in a sunlit street adorned with campaign banners of the Libertarian presidential candidate. People are voting and dropping ballots into a ballot box nearby. At an auto repair shop, a mechanic inspects a parking brake system with a smile, indicating no issues. Create an atmosphere filled with freedom and ease, depicting a smooth coexistence of voting and well-functioning parking brakes amidst the political climate. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from A Disney Movie Whimsical illustration a funny image macro Cyberpunk Sci-fi fantacy
ChatGPT: a funny image macro

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake, in the following situation: As the level of political freedom rhetoric in the state decreased, the molecules in the air became less likely to engage in rebellious behavior. This led to a harmonious alignment of atomic particles within the parking brake systems, effectively reducing the need for recalls. It's as if the ideologies of individual choice and limited government intervention had a direct impact on the mechanical operations of parked vehicles. Who would have thought that the political climate could pump the brakes on automotive malfunctions? Remember, when it comes to liberty and parking brakes, every vote counts!. Keep the description simple.
ChatGPT: We see cars parked on the streets of California, bathed in warm sunlight. The Libertarian presidential candidate's campaign banners adorn the parked cars, and as people walk by, they are dropping ballots into a nearby ballot box. Meanwhile, in an auto repair shop, a mechanic is inspecting a parking brake system with a smile on their face, as they find no issues with it. The air around the cars and the garage seems to be filled with a sense of freedom and ease, as if the political climate has brought about a harmonious and smooth functioning of both voting and parking brakes.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ a funny image macro ] and depicting this scene: We see cars parked on the streets of California, bathed in warm sunlight. The Libertarian presidential candidate's campaign banners adorn the parked cars, and as people walk by, they are dropping ballots into a nearby ballot box. Meanwhile, in an auto repair shop, a mechanic is inspecting a parking brake system with a smile on their face, as they find no issues with it. The air around the cars and the garage seems to be filled with a sense of freedom and ease, as if the political climate has brought about a harmonious and smooth functioning of both voting and parking brakes. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image portraying a lighthearted and harmonious scene in California. Show parked cars in a sunlit street adorned with campaign banners of the Libertarian presidential candidate. People are voting and dropping ballots into a ballot box nearby. At an auto repair shop, a mechanic inspects a parking brake system with a smile, indicating no issues. Create an atmosphere filled with freedom and ease, depicting a smooth coexistence of voting and well-functioning parking brakes amidst the political climate.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Votes for the Libertarian Presidential candidate in California caused Automotive recalls for issues with the Parking Brake to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California

The Journal of Political Automotive Engineering

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and US DOT to assess this nagging question. You found a correlation coefficient of 0.8673699 and p < 0.01 for 1980 to 2020.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the labyrinthine world of automotive safety, where the intricate workings of brakes and parkings are scrutinized with quizzical intensity, one might not expect to encounter the colorful tapestry of politics. The balletic flutterings of political preferences, akin to a butterfly's capricious flight, may seem worlds apart from the stoic mechanisms that govern recalls and safety protocols in the automotive sphere. However, as we peel back the layers of this kaleidoscopic research, a peculiar and unexpected relationship unfurls before us, akin to discovering a parking brake in the midst of the political highway.

The duality of this relationship between political votes and parking brake recalls in the enigmatic state of California is compelling on a multitude of levels. It beckons us to ponder the possibility that the very act of casting a vote may send ripples through the intricate fabric of automotive safety, much like a rock tossed into a serene pond. Our intention with this research is not only to unfurl this unexpected narrative but to also offer a slightly offbeat perspective to the rather staid domains of politics and automotive safety.

As we delve into the findings of this study, we invite the reader to don their proverbial detective hats and take a merry plunge into the convoluted dance between political ideologies and parking brake recalls. With hints of statistical significance and gossamer threads of correlation, we aim to paint a vibrant canvas that not only contributes to the academic discourse but also sparks a chuckle or two for the savvy observer.

So, without further ado, let us embark on this whimsical journey through the intermingled saga of political votes and parking brake recalls, and perhaps uncover some unanticipated treasures along the way.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the labyrinthine world of automotive safety, where the intricate workings of brakes and parkings are scrutinized with quizzical intensity, one might not expect to encounter the colorful tapestry of politics. The balletic flutterings of political preferences, akin to a butterfly's capricious flight, may seem worlds apart from the stoic mechanisms that govern recalls and safety protocols in the automotive sphere. However, as we peel back the layers of this kaleidoscopic research, a peculiar and unexpected relationship unfurls before us, akin to discovering a parking brake in the midst of the political highway.
The duality of this relationship between political votes and parking brake recalls in the enigmatic state of California is compelling on a multitude of levels. It beckons us to ponder the possibility that the very act of casting a vote may send ripples through the intricate fabric of automotive safety, much like a rock tossed into a serene pond. Our intention with this research is not only to unfurl this unexpected narrative but to also offer a slightly offbeat perspective to the rather staid domains of politics and automotive safety.
As we delve into the findings of this study, we invite the reader to don their proverbial detective hats and take a merry plunge into the convoluted dance between political ideologies and parking brake recalls. With hints of statistical significance and gossamer threads of correlation, we aim to paint a vibrant canvas that not only contributes to the academic discourse but also sparks a chuckle or two for the savvy observer.
So, without further ado, let us embark on this whimsical journey through the intermingled saga of political votes and parking brake recalls, and perhaps uncover some unanticipated treasures along the way.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The initial inclinations toward the unusual amalgamation of political proclivities and automotive maladies were rooted in the works of Smith (2005), Doe (2010), and Jones (2013). However, it was not until the research team stumbled upon "The Political Brake: How Political Choices Impact Automotive Safety" by Lorem and Ipsum (2017) that the true potential of this interplay started to come to fruition. Lorem and Ipsum's seminal work delves into the intricate dynamics of political decision-making and its uncanny influence on the safety protocols of modern automobiles. Their incisive analysis of statistically significant correlations between political voting patterns and the frequency of automotive recalls piqued the interest of the research team, prompting a deeper exploration into this uncharted territory.

As the research unfolded, it became evident that the intersection of political behavior and automotive safety was a playground for hidden connections and unexpected revelations. The authors stumbled across "The Brake of Politics: A Study on the Impact of Political Affiliation on Automotive Functions" by Fictional (2015), a work of fiction that offers a remarkably prescient insight into the curious relationship between political leanings and the functionality of automotive systems. Although a work of fiction, the parallels drawn between the whimsical world of politics and the pragmatic landscape of automotive mechanics provided a whimsical yet thought-provoking perspective that cannot be disregarded.

Further insight into the undercurrents of this peculiar association was uncovered in an unexpected source – social media. The research team encountered an intriguing tweet by @CarEnthusiast_99, which humorously quipped, "Are parking brake recalls just the political parties pulling our legs? #BrakeTheVote." Although ostensibly lighthearted, this social media snippet served as a poignant reminder of the widespread intrigue and speculation surrounding the nexus between political influences and automotive recalls. It underscored the notion that beneath the veneer of serious academic discourse lies a rich tapestry of conjecture, imagination, and unexpected amusement.

As the journey through this uncharted territory continues, our research is poised to elucidate the enigmatic relationship between casting a vote and the functionality of the parking brake, unearthing chuckles and insights alike from the seemingly disparate worlds of politics and automotive safety.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and US DOT . You used data from 1980 to 2020

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

[[INTRODUCTION]]
In the labyrinthine world of automotive safety, where the intricate workings of brakes and parkings are scrutinized with quizzical intensity, one might not expect to encounter the colorful tapestry of politics. The balletic flutterings of political preferences, akin to a butterfly's capricious flight, may seem worlds apart from the stoic mechanisms that govern recalls and safety protocols in the automotive sphere. However, as we peel back the layers of this kaleidoscopic research, a peculiar and unexpected relationship unfurls before us, akin to discovering a parking brake in the midst of the political highway.
The duality of this relationship between political votes and parking brake recalls in the enigmatic state of California is compelling on a multitude of levels. It beckons us to ponder the possibility that the very act of casting a vote may send ripples through the intricate fabric of automotive safety, much like a rock tossed into a serene pond. Our intention with this research is not only to unfurl this unexpected narrative but to also offer a slightly offbeat perspective to the rather staid domains of politics and automotive safety.
As we delve into the findings of this study, we invite the reader to don their proverbial detective hats and take a merry plunge into the convoluted dance between political ideologies and parking brake recalls. With hints of statistical significance and gossamer threads of correlation, we aim to paint a vibrant canvas that not only contributes to the academic discourse but also sparks a chuckle or two for the savvy observer.
So, without further ado, let us embark on this whimsical journey through the intermingled saga of political votes and parking brake recalls, and perhaps uncover some unanticipated treasures along the way.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To untangle the perplexing web of political choices and automotive safety, our research team embarked on a convoluted yet jovial journey through the annals of data collection and statistical analysis. The data used in this study was primarily sourced from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation for the period spanning from 1980 to 2020.

The first step in our methodology involved engaging in an intricate dance of data collection and curation, akin to orchestrating a symphony with strings of digits and bytes. We meticulously combed through historical election data to gather information on the votes secured by the Libertarian presidential candidate in California. This data, much like a fine wine, was allowed to breathe and reveal its intricate flavors to us.

Simultaneously, our team delved into the enigmatic world of automotive recalls, specifically focusing on issues related to the parking brake. We combed through the records from the US DOT, seeking out the instances where automotive manufacturers had to perform the familiar and dreaded "recall dance" due to parking brake malfunctions.

Once the raw data was corralled, it was time to unleash the power of statistical analysis upon it. We employed a robust and sophisticated analytical arsenal, which, much like a Swiss Army knife, had a tool for every occasion. The renowned and reclusive Pearson's correlation coefficient was summoned to gauge the strength and direction of the relationship between votes for the Libertarian candidate and parking brake recalls.

The statistical significance of our findings was buttressed by the utilization of a p-value less than 0.01, signaling that the correlation observed was indeed not a mere figment of statistical noise. It was akin to finding a needle in a haystack, only to realize that the needle had been persistently tugging at the threads of correlation all along.

Finally, we conducted a series of robustness tests and sensitivity analyses to ensure that our findings held their ground even under the scrutinizing gaze of potential confounding variables. This, much like a sturdy fortress withstands the battering ram of uncertainty, ensured that our conclusions were fortified against the whims of serendipity.

In essence, our methodology was as labyrinthine and intricate as the relationship we sought to explore. It involved a harmonious blend of data wrangling, statistical prowess, and a dash of whimsy – much like a well-crafted piece of literature that leaves the reader simultaneously enlightened and entertained.



Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and US DOT .

For the time period 1980 to 2020, you found a correlation 0.8673699, r-squared of 0.7523305, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the labyrinthine world of automotive safety, where the intricate workings of brakes and parkings are scrutinized with quizzical intensity, one might not expect to encounter the colorful tapestry of politics. The balletic flutterings of political preferences, akin to a butterfly's capricious flight, may seem worlds apart from the stoic mechanisms that govern recalls and safety protocols in the automotive sphere. However, as we peel back the layers of this kaleidoscopic research, a peculiar and unexpected relationship unfurls before us, akin to discovering a parking brake in the midst of the political highway.
The duality of this relationship between political votes and parking brake recalls in the enigmatic state of California is compelling on a multitude of levels. It beckons us to ponder the possibility that the very act of casting a vote may send ripples through the intricate fabric of automotive safety, much like a rock tossed into a serene pond. Our intention with this research is not only to unfurl this unexpected narrative but to also offer a slightly offbeat perspective to the rather staid domains of politics and automotive safety.
As we delve into the findings of this study, we invite the reader to don their proverbial detective hats and take a merry plunge into the convoluted dance between political ideologies and parking brake recalls. With hints of statistical significance and gossamer threads of correlation, we aim to paint a vibrant canvas that not only contributes to the academic discourse but also sparks a chuckle or two for the savvy observer.
So, without further ado, let us embark on this whimsical journey through the intermingled saga of political votes and parking brake recalls, and perhaps uncover some unanticipated treasures along the way.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis revealed a remarkably robust correlation of 0.8673699 between the votes obtained by the Libertarian presidential candidate in California and the occurrence of automotive recalls concerning the parking brake. This finding, supported by an r-squared value of 0.7523305, exudes a level of coherence that rivals the harmony between a car and its smoothly functioning parking brake.

Fig. 1 illustrates the unmistakable relationship between these seemingly unrelated variables. The scatterplot showcases a pattern reminiscent of two dancers moving in harmonious synchrony, with each increase in votes for the Libertarian candidate accompanied by a corresponding surge in parking brake recalls. The data points, akin to protagonists in an enthralling narrative, weave a tale of unexpected camaraderie between the world of politics and the realm of automotive safety.

The agreement between the data and the proposed model was found to be statistically significant, with a p-value of less than 0.01. This robust level of significance is akin to stumbling upon an undiscovered treasure trove in the midst of a rather mundane search—a delightful surprise that adds a touch of whimsy to the otherwise serious field of statistical analysis.

The implications of these findings extend beyond the confines of statistical relations. They beckon us to consider the potential interplay between political inclinations and safety measures in the automotive domain, offering a delightful twist to the conventional narrative of vehicle recalls. This unexpected correlation may open avenues for future research and evoke a wry smile from those who find joy in uncovering the unexpected.

In summary, our investigation presents a compelling case for the intertwined nature of political preferences and automotive safety, emphasizing the need for a multidisciplinary approach in understanding the complexities of societal systems. The dance between votes and recalls, while surprising, serves as a delightful reminder of the colorful and intricate connections that permeate our world.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

[[LITERATURE REVIEW]]
The initial inclinations toward the unusual amalgamation of political proclivities and automotive maladies were rooted in the works of Smith (2005), Doe (2010), and Jones (2013). However, it was not until the research team stumbled upon "The Political Brake: How Political Choices Impact Automotive Safety" by Lorem and Ipsum (2017) that the true potential of this interplay started to come to fruition. Lorem and Ipsum's seminal work delves into the intricate dynamics of political decision-making and its uncanny influence on the safety protocols of modern automobiles. Their incisive analysis of statistically significant correlations between political voting patterns and the frequency of automotive recalls piqued the interest of the research team, prompting a deeper exploration into this uncharted territory.
As the research unfolded, it became evident that the intersection of political behavior and automotive safety was a playground for hidden connections and unexpected revelations. The authors stumbled across "The Brake of Politics: A Study on the Impact of Political Affiliation on Automotive Functions" by Fictional (2015), a work of fiction that offers a remarkably prescient insight into the curious relationship between political leanings and the functionality of automotive systems. Although a work of fiction, the parallels drawn between the whimsical world of politics and the pragmatic landscape of automotive mechanics provided a whimsical yet thought-provoking perspective that cannot be disregarded.
Further insight into the undercurrents of this peculiar association was uncovered in an unexpected source – social media. The research team encountered an intriguing tweet by @CarEnthusiast_99, which humorously quipped, "Are parking brake recalls just the political parties pulling our legs? #BrakeTheVote." Although ostensibly lighthearted, this social media snippet served as a poignant reminder of the widespread intrigue and speculation surrounding the nexus between political influences and automotive recalls. It underscored the notion that beneath the veneer of serious academic discourse lies a rich tapestry of conjecture, imagination, and unexpected amusement.
As the journey through this uncharted territory continues, our research is poised to elucidate the enigmatic relationship between casting a vote and the functionality of the parking brake, unearthing chuckles and insights alike from the seemingly disparate worlds of politics and automotive safety.

[[RESULTS]]
The statistical analysis revealed a remarkably robust correlation of 0.8673699 between the votes obtained by the Libertarian presidential candidate in California and the occurrence of automotive recalls concerning the parking brake. This finding, supported by an r-squared value of 0.7523305, exudes a level of coherence that rivals the harmony between a car and its smoothly functioning parking brake.
Fig. 1 illustrates the unmistakable relationship between these seemingly unrelated variables. The scatterplot showcases a pattern reminiscent of two dancers moving in harmonious synchrony, with each increase in votes for the Libertarian candidate accompanied by a corresponding surge in parking brake recalls. The data points, akin to protagonists in an enthralling narrative, weave a tale of unexpected camaraderie between the world of politics and the realm of automotive safety.
The agreement between the data and the proposed model was found to be statistically significant, with a p-value of less than 0.01. This robust level of significance is akin to stumbling upon an undiscovered treasure trove in the midst of a rather mundane search—a delightful surprise that adds a touch of whimsy to the otherwise serious field of statistical analysis.
The implications of these findings extend beyond the confines of statistical relations. They beckon us to consider the potential interplay between political inclinations and safety measures in the automotive domain, offering a delightful twist to the conventional narrative of vehicle recalls. This unexpected correlation may open avenues for future research and evoke a wry smile from those who find joy in uncovering the unexpected.
In summary, our investigation presents a compelling case for the intertwined nature of political preferences and automotive safety, emphasizing the need for a multidisciplinary approach in understanding the complexities of societal systems. The dance between votes and recalls, while surprising, serves as a delightful reminder of the colorful and intricate connections that permeate our world.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study has unearthed a fascinating connection between political preferences and automotive safety, adding an unexpected twist to the conventional understanding of vehicle recalls. The robust correlation coefficient of 0.8673699, along with the statistically significant p-value, underscores the compelling relationship between the votes garnered by the Libertarian presidential candidate in California and the frequency of parking brake recalls. This finding not only aligns with prior investigations by Smith (2005), Doe (2010), and Jones (2013) but also extends far beyond the realm of statistical coherency.

The unanticipated camaraderie between politics and automotive safety, reminiscent of a duo dancing in harmonious synchrony, has left us pondering the potential implications and underlying mechanisms of this peculiar association. Lorem and Ipsum's work (2017) laid the groundwork for our investigation, shedding light on the intricate dynamics of political decision-making and its uncanny influence on automotive safety. Their impactful analysis not only set the stage for our findings but also revealed the depth of relationships hidden beneath the veneer of seemingly disparate domains.

In alignment with the prescient insights of Fictional (2015), our study delves into the whimsical yet thought-provoking perspective that piqued our interest in this curious relationship. Moreover, the serendipitous encounter with @CarEnthusiast_99's tweet, while seemingly lighthearted, serves as a poignant reminder of the widespread intrigue and speculation surrounding the nexus between political influences and automotive recalls. As we journeyed through this uncharted territory, it became evident that beneath the serious academic discourse lies a rich tapestry of conjecture, imagination, and unexpected amusement illuminated by seemingly speculative sources.

Our findings not only reaffirm the correlations identified by previous researchers but also invite further exploration into the undercurrents of this unique nexus. The data points, akin to protagonists in an enthralling narrative, weave a tale of unexpected camaraderie between politics and automotive safety, challenging the conventional wisdom and delighting those who relish uncovering the unexpected. This unexpected correlation may open avenues for future research, offering a delightful twist to the traditional narrative of vehicle recalls and underscoring the whimsical yet compelling connections that permeate our world.

In light of these findings, it is essential to adopt a multidisciplinary approach in understanding the complexities of societal systems. The dance between votes and recalls, while surprising, serves as a delightful reminder of the colorful and intricate connections that transcend traditional boundaries. As we ponder the implications of this peculiar association, we are left with a wry smile and an insatiable curiosity for the underlying mechanisms driving this unexpected correlation.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in California and Automotive recalls for issues with the Parking Brake. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California"

[[ABSTRACT]]
In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

[[INTRDUCTION]]
In the labyrinthine world of automotive safety, where the intricate workings of brakes and parkings are scrutinized with quizzical intensity, one might not expect to encounter the colorful tapestry of politics. The balletic flutterings of political preferences, akin to a butterfly's capricious flight, may seem worlds apart from the stoic mechanisms that govern recalls and safety protocols in the automotive sphere. However, as we peel back the layers of this kaleidoscopic research, a peculiar and unexpected relationship unfurls before us, akin to discovering a parking brake in the midst of the political highway.
The duality of this relationship between political votes and parking brake recalls in the enigmatic state of California is compelling on a multitude of levels. It beckons us to ponder the possibility that the very act of casting a vote may send ripples through the intricate fabric of automotive safety, much like a rock tossed into a serene pond. Our intention with this research is not only to unfurl this unexpected narrative but to also offer a slightly offbeat perspective to the rather staid domains of politics and automotive safety.
As we delve into the findings of this study, we invite the reader to don their proverbial detective hats and take a merry plunge into the convoluted dance between political ideologies and parking brake recalls. With hints of statistical significance and gossamer threads of correlation, we aim to paint a vibrant canvas that not only contributes to the academic discourse but also sparks a chuckle or two for the savvy observer.
So, without further ado, let us embark on this whimsical journey through the intermingled saga of political votes and parking brake recalls, and perhaps uncover some unanticipated treasures along the way.

[[RESULTS]]
The statistical analysis revealed a remarkably robust correlation of 0.8673699 between the votes obtained by the Libertarian presidential candidate in California and the occurrence of automotive recalls concerning the parking brake. This finding, supported by an r-squared value of 0.7523305, exudes a level of coherence that rivals the harmony between a car and its smoothly functioning parking brake.
Fig. 1 illustrates the unmistakable relationship between these seemingly unrelated variables. The scatterplot showcases a pattern reminiscent of two dancers moving in harmonious synchrony, with each increase in votes for the Libertarian candidate accompanied by a corresponding surge in parking brake recalls. The data points, akin to protagonists in an enthralling narrative, weave a tale of unexpected camaraderie between the world of politics and the realm of automotive safety.
The agreement between the data and the proposed model was found to be statistically significant, with a p-value of less than 0.01. This robust level of significance is akin to stumbling upon an undiscovered treasure trove in the midst of a rather mundane search—a delightful surprise that adds a touch of whimsy to the otherwise serious field of statistical analysis.
The implications of these findings extend beyond the confines of statistical relations. They beckon us to consider the potential interplay between political inclinations and safety measures in the automotive domain, offering a delightful twist to the conventional narrative of vehicle recalls. This unexpected correlation may open avenues for future research and evoke a wry smile from those who find joy in uncovering the unexpected.
In summary, our investigation presents a compelling case for the intertwined nature of political preferences and automotive safety, emphasizing the need for a multidisciplinary approach in understanding the complexities of societal systems. The dance between votes and recalls, while surprising, serves as a delightful reminder of the colorful and intricate connections that permeate our world.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unveiled a truly remarkable correlation between the votes for the Libertarian presidential candidate in California and the frequency of automotive recalls pertaining to issues with the parking brake. The statistical significance of the correlation coefficient, paired with the tantalizingly small p-value, underlines the intriguing relationship between political preferences and automotive safety—truly a case of politics "brake-ing" into the realm of automotive recalls. The unexpected camaraderie between these seemingly disparate domains not only challenges conventional wisdom but also tickles the fancy of those who savor the flavor of unpredictability in scholarly pursuits.

The implications of our findings, much like a well-timed punchline, go beyond the boundaries of traditional academic discourse. The interplay between political inclinations and safety measures in the automotive domain presents a lively jigsaw puzzle for future researchers to piece together, adding a dash of spice to the often staid landscape of statistical investigations. However, let's not pump the brakes on this lively correlation just yet. It's clear that our findings have revved up some thought-provoking considerations about the ripple effects of political actions on unexpected facets of society.

In light of the robust correlation and statistical significance demonstrated in our study, we can confidently assert that no further research is needed in this area. Just kidding! As scholars, we must acknowledge that the joy of discovery lies in the perpetual quest for knowledge. Nevertheless, for now, we can revel in the whimsical allure of this correlation, recognizing that sometimes, the most enthralling discoveries emerge from the unlikeliest of intersections. With that, let's bid adieu to this peculiar dance between politics and parking brakes and steer our scholarly pursuits toward the next enigmatic conundrum.


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Automotive Engineering


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Political and Automotive Research


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Brake-ing the Mold: The Libertarian Candidate's Influence on Parking Brake Recalls in California with an abstract of In the realm of automotive safety, the functionality and reliability of parking brakes are vital. However, amidst the serious considerations surrounding automotive recalls, one might not expect to encounter the world of politics. This paper explores the remarkable correlation between the votes garnered by the Libertarian presidential candidate in California and the frequency of automotive recalls related to issues with the parking brake. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our research team delved into decades of collected information to uncover an unexpected relationship between political preferences and automotive safety. The statistically significant correlation coefficient of 0.8673699, accompanying a p-value of less than 0.01, from 1980 to 2020, sheds light on this peculiar association. Our findings not only highlight the intertwined nature of seemingly disparate domains but also raise amusing possibilities for political and automotive enthusiasts alike.

ChatGPT:

parking brake recalls, automotive safety, Libertarian presidential candidate votes, California, MIT Election Data and Science Lab, Harvard Dataverse, US DOT, political preferences, correlation coefficient, statistical significance, automotive recalls, political influence, automotive safety research, political impact on recalls

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.



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Data details

Votes for the Libertarian Presidential candidate in California
Detailed data title: Percentage of all votes cast for the Libertarian Presidential candidate in California
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Libertarian Presidential candidate in California

Automotive recalls for issues with the Parking Brake
Source: US DOT
See what else correlates with Automotive recalls for issues with the Parking Brake

Correlation r = 0.8673699 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r2 = 0.7523305 (Coefficient of determination)
This means 75.2% of the change in the one variable (i.e., Automotive recalls for issues with the Parking Brake) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in California) over the 10 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0011. 0.0011499954867787222000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.87 in 0.11% of random cases. Said differently, if you correlated 870 random variables Which I absolutely did.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.52, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
1980198819921996200020042008201220162020
Votes for the Libertarian Presidential candidate in California (Percentage of votes)1.72890.7090580.4324490.734570.4151080.4038610.4983231.098443.374091.07363
Automotive recalls for issues with the Parking Brake (Recalls)521666872810




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1.7289,0.709058,0.432449,0.73457,0.415108,0.403861,0.498323,1.09844,3.37409,1.07363,])
array_2 = np.array([5,2,1,6,6,6,8,7,28,10,])
array_1_name = "Votes for the Libertarian Presidential candidate in California"
array_2_name = "Automotive recalls for issues with the Parking Brake"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)



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You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

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Correlation ID: 4470 · Black Variable ID: 26062 · Red Variable ID: 1113
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