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Spurious correlation #1,215 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Jarred and the second variable is Arson in Rhode Island.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

Fewer people naming their kids Jarred means fewer potential troublemakers with a penchant for playing with fire, keeping the arson incidents in check in the Ocean State. After all, it's a well-known fact that the name Jarred has a fiery ring to it, and without as many little Jarreds running around, Rhode Island can breathe a little easier.

Model: dalle-3
Prompt: [ Concept art ] Create an image of a serene park with a prominent sign that reads "Arson Incidents." In the background, there's a group of people wearing "Jarred" t-shirts. As the number of people wearing "Jarred" t-shirts decreases, the group becomes smaller, and the sign for "Arson Incidents" also starts to fade and becomes less visible, indicating a decrease in arson incidents. The scene suggests that as the number of people named Jarred decreases, the potential for arson also decreases, creating a calmer and safer park environment. Capture the transition from a larger group to a smaller group and the fading of the "Arson Incidents" sign to convey the correlation between the two elements. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: A decrease in the popularity of the first name Jarred caused arson in Rhode Island to also decrease because as the name Jarred became less common, so did the desire to "fire up" any questionable activities. With fewer people named Jarred around, there were fewer "hotheads" to start trouble, leading to a decrease in arson incidents. It seems that the lack of Jarr-ed up individuals had a cooling effect on the arson statistics, extinguishing the flames of mischief in Rhode Island.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: a Polaroid photo Concept art Futuristic Celtic art Art nouveau
ChatGPT: Concept art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. A decrease in the popularity of the first name Jarred caused arson in Rhode Island to also decrease because as the name Jarred became less common, so did the desire to "fire up" any questionable activities. With fewer people named Jarred around, there were fewer "hotheads" to start trouble, leading to a decrease in arson incidents. It seems that the lack of Jarr-ed up individuals had a cooling effect on the arson statistics, extinguishing the flames of mischief in Rhode Island.
ChatGPT: Imagine a park with a large sign that reads "Arson Incidents." In the background, there is a group of people with the name "Jarred" on their t-shirts. As the number of people wearing "Jarred" t-shirts decreases, the group becomes smaller, and the sign for "Arson Incidents" also starts to fade and becomes less visible, indicating a decrease in arson incidents. The scene suggests that as the number of people named Jarred decreases, the potential for arson also decreases, creating a calmer and safer park environment.

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: [ Concept art ] and depicting this scene: Imagine a park with a large sign that reads "Arson Incidents." In the background, there is a group of people with the name "Jarred" on their t-shirts. As the number of people wearing "Jarred" t-shirts decreases, the group becomes smaller, and the sign for "Arson Incidents" also starts to fade and becomes less visible, indicating a decrease in arson incidents. The scene suggests that as the number of people named Jarred decreases, the potential for arson also decreases, creating a calmer and safer park environment. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Concept art ] Create an image of a serene park with a prominent sign that reads "Arson Incidents." In the background, there's a group of people wearing "Jarred" t-shirts. As the number of people wearing "Jarred" t-shirts decreases, the group becomes smaller, and the sign for "Arson Incidents" also starts to fade and becomes less visible, indicating a decrease in arson incidents. The scene suggests that as the number of people named Jarred decreases, the potential for arson also decreases, creating a calmer and safer park environment. Capture the transition from a larger group to a smaller group and the fading of the "Arson Incidents" sign to convey the correlation between the two elements.

*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 Popularity of the first name Jarred caused Arson in Rhode Island to decrease.

AI academic paper

(Because p < 0.01)
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

Journal of Forensic Psychology and Criminology

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from US Social Security Administration and FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.9564808 and p < 0.01 for 1985 to 2022.

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]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The etymology of names has long been a topic of fascination, often inviting conjecture about the influence of nomenclature on personal characteristics and behavior. While popular culture and anecdotal evidence frequently offer colorful narratives about the impact of names on one's destiny, empirical research in this domain has been rather sparse. This study delves into the intriguing intersection of nomenclature and criminal behavior, focusing specifically on the relationship between the prevalence of the first name "Jarred" and the incidence of arson in the state of Rhode Island.

Perhaps it is serendipitous that the confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services has illuminated a compelling correlation, resembling a veritable firework display in the realm of statistical analysis. The scorching correlation coefficient of 0.9564808, coupled with a p-value less than 0.01, suggests a conspicuous association between the popularity of the name "Jarred" and the occurrence of arson in the Ocean State. The sheer heat emitted by this statistical relationship steers our inquiry into uncharted territory, where the flickering flames of curiosity are kindled.

It is akin to navigating through the smoky haze of empirical ambiguity, seeking to discern whether the fervor of names can indeed ignite criminal propensities or whether this incendiary correlation is merely a chance alignment of factors. Nevertheless, as we embark on this scholarly expedition, it is imperative to maintain a cautious stance, wary of falsely inferring causation from correlation. For if the mere mention of a name could stoke criminal proclivities, one might wonder whether other appellations harbor dormant potential for mischief, or whether certain names have a "spark" of criminality hidden within their syllables.

Amidst the smoldering embers of empirical inquiry, this study ignites a fervent call for further investigation into the potential influence of names on criminal conduct. As we plunge into the depths of this scorching correlation, we are poised to unravel the enigmatic ties between nomenclature and nefarious acts, bearing witness to the captivating dance of data and the fiery allure of statistical inquiry.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The etymology of names has long been a topic of fascination, often inviting conjecture about the influence of nomenclature on personal characteristics and behavior. While popular culture and anecdotal evidence frequently offer colorful narratives about the impact of names on one's destiny, empirical research in this domain has been rather sparse. This study delves into the intriguing intersection of nomenclature and criminal behavior, focusing specifically on the relationship between the prevalence of the first name "Jarred" and the incidence of arson in the state of Rhode Island.
Perhaps it is serendipitous that the confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services has illuminated a compelling correlation, resembling a veritable firework display in the realm of statistical analysis. The scorching correlation coefficient of 0.9564808, coupled with a p-value less than 0.01, suggests a conspicuous association between the popularity of the name "Jarred" and the occurrence of arson in the Ocean State. The sheer heat emitted by this statistical relationship steers our inquiry into uncharted territory, where the flickering flames of curiosity are kindled.
It is akin to navigating through the smoky haze of empirical ambiguity, seeking to discern whether the fervor of names can indeed ignite criminal propensities or whether this incendiary correlation is merely a chance alignment of factors. Nevertheless, as we embark on this scholarly expedition, it is imperative to maintain a cautious stance, wary of falsely inferring causation from correlation. For if the mere mention of a name could stoke criminal proclivities, one might wonder whether other appellations harbor dormant potential for mischief, or whether certain names have a "spark" of criminality hidden within their syllables.
Amidst the smoldering embers of empirical inquiry, this study ignites a fervent call for further investigation into the potential influence of names on criminal conduct. As we plunge into the depths of this scorching correlation, we are poised to unravel the enigmatic ties between nomenclature and nefarious acts, bearing witness to the captivating dance of data and the fiery allure of statistical inquiry.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The authors find that, despite the unconventional nature of our inquiry, the nexus between the prevalence of the first name "Jarred" and the incidence of arson in Rhode Island has drawn parallels with other studies exploring the influence of nomenclature on behavior. In "The Name Game: Cultural Signifiers and Psychological Impact," Smith and Doe delve into the societal perceptions and psychological implications associated with individuals' names, shedding light on the multifaceted dimensions of nomenclature. Similarly, Jones' work, "Appellations and Actions: Untangling the Web of Name and Behavior," offers a nuanced exploration of the interplay between names and behavior, albeit within a broader context.

Transitioning from the realm of scholarly research, popular non-fiction books such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner have captivated audiences with their unconventional lens on causation and correlation, engaging readers in a discourse that resonates with our investigative approach. Furthermore, the curious intersection of human behavior and nomenclature has found its place in fictional literature, with works such as "The Name of the Rose" by Umberto Eco and "The Shadow of the Wind" by Carlos Ruiz Zafón inviting readers into enigmatic narratives that subtly intertwine names with elusive fates.

Inspiration can also be drawn from board games such as "Clue," where the search for culprits and motives mirrors our scholarly pursuit of untangling the enigmatic ties between the prevalence of the name "Jarred" and the occurrence of arson in Rhode Island. The whimsical intrigue of board game dynamics offers a lighthearted reflection of our more serious inquiry, nudging us to ponder whether certain names may harbor clues to clandestine propensities or if the correlation we observe is a mere roll of the dice in the game of statistical analysis.

As the embers of empirical curiosity continue to flicker, this review sets the stage for a deeper exploration of the incendiary links between names and criminal acts, punctuating our scholarly inquiry with a touch of playful contemplation amidst the somber backdrop of statistical investigation.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and FBI Criminal Justice Information Services . You used data from 1985 to 2022

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]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

[[INTRODUCTION]]
The etymology of names has long been a topic of fascination, often inviting conjecture about the influence of nomenclature on personal characteristics and behavior. While popular culture and anecdotal evidence frequently offer colorful narratives about the impact of names on one's destiny, empirical research in this domain has been rather sparse. This study delves into the intriguing intersection of nomenclature and criminal behavior, focusing specifically on the relationship between the prevalence of the first name "Jarred" and the incidence of arson in the state of Rhode Island.
Perhaps it is serendipitous that the confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services has illuminated a compelling correlation, resembling a veritable firework display in the realm of statistical analysis. The scorching correlation coefficient of 0.9564808, coupled with a p-value less than 0.01, suggests a conspicuous association between the popularity of the name "Jarred" and the occurrence of arson in the Ocean State. The sheer heat emitted by this statistical relationship steers our inquiry into uncharted territory, where the flickering flames of curiosity are kindled.
It is akin to navigating through the smoky haze of empirical ambiguity, seeking to discern whether the fervor of names can indeed ignite criminal propensities or whether this incendiary correlation is merely a chance alignment of factors. Nevertheless, as we embark on this scholarly expedition, it is imperative to maintain a cautious stance, wary of falsely inferring causation from correlation. For if the mere mention of a name could stoke criminal proclivities, one might wonder whether other appellations harbor dormant potential for mischief, or whether certain names have a "spark" of criminality hidden within their syllables.
Amidst the smoldering embers of empirical inquiry, this study ignites a fervent call for further investigation into the potential influence of names on criminal conduct. As we plunge into the depths of this scorching correlation, we are poised to unravel the enigmatic ties between nomenclature and nefarious acts, bearing witness to the captivating dance of data and the fiery allure of statistical inquiry.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

The first stage of this research endeavor involved obtaining data from the US Social Security Administration and the FBI Criminal Justice Information Services, both renowned repositories of demographic and criminal statistics. The US Social Security Administration provided us with comprehensive information regarding the prevalence of the first name "Jarred" in Rhode Island from 1985 to 2022. Leveraging this data, we applied a bewildering array of statistical techniques to elucidate trends and patterns in the popularity of the name "Jarred" over the years, navigating through the labyrinthine corridors of nomenclature dynamics.

Simultaneously, we delved into the FBI Criminal Justice Information Services database, extracting incendiary details of arson incidents in the state of Rhode Island during the same temporal expanse. This entailed sifting through a conflagration of information, untangling the intricate web of arson occurrences and their contextual backdrop, grasping the fiery threads of criminal activity woven through the tapestry of data.

With the fervor of statistical analysis alight within us, we employed a perplexing concoction of quantitative methods, setting ablaze the field of inferential statistics. The scorching heat of correlation coefficients, infernal flames of regression analyses, and the smoldering embers of hypothesis testing were our guiding beacons as we navigated the treacherous terrain of data analysis. Furthermore, a multifaceted exploration of time series analysis was undertaken, casting light on the temporal dynamics of arson incidents vis-à-vis the waxing and waning popularity of the name "Jarred".

The resulting datasets were subjected to a veritable inferno of statistical scrutiny, with the searing gaze of significance testing and the blistering heat of confidence intervals illuminating the path towards uncovering meaningful relationships. The culmination of these tumultuous analyses yielded a scintillating correlation coefficient of 0.9564808, engendering astonishment at the dazzling intensity of this infernal association between the name "Jarred" and instances of arson in Rhode Island.

Upon deciphering this enigmatic correlation, we found ourselves standing at the precipice of empirical revelation, peering into the incandescent heart of our findings. While we exercise caution in attributing causality to this scorching association, the allure of its statistical radiance beckons us to traverse the tempestuous terrain of further inquiry, seeking to elucidate the burgeoning conflagration of nomenclature and nefarious deeds.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and FBI Criminal Justice Information Services .

For the time period 1985 to 2022, you found a correlation 0.9564808, r-squared of 0.9148556, 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]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The etymology of names has long been a topic of fascination, often inviting conjecture about the influence of nomenclature on personal characteristics and behavior. While popular culture and anecdotal evidence frequently offer colorful narratives about the impact of names on one's destiny, empirical research in this domain has been rather sparse. This study delves into the intriguing intersection of nomenclature and criminal behavior, focusing specifically on the relationship between the prevalence of the first name "Jarred" and the incidence of arson in the state of Rhode Island.
Perhaps it is serendipitous that the confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services has illuminated a compelling correlation, resembling a veritable firework display in the realm of statistical analysis. The scorching correlation coefficient of 0.9564808, coupled with a p-value less than 0.01, suggests a conspicuous association between the popularity of the name "Jarred" and the occurrence of arson in the Ocean State. The sheer heat emitted by this statistical relationship steers our inquiry into uncharted territory, where the flickering flames of curiosity are kindled.
It is akin to navigating through the smoky haze of empirical ambiguity, seeking to discern whether the fervor of names can indeed ignite criminal propensities or whether this incendiary correlation is merely a chance alignment of factors. Nevertheless, as we embark on this scholarly expedition, it is imperative to maintain a cautious stance, wary of falsely inferring causation from correlation. For if the mere mention of a name could stoke criminal proclivities, one might wonder whether other appellations harbor dormant potential for mischief, or whether certain names have a "spark" of criminality hidden within their syllables.
Amidst the smoldering embers of empirical inquiry, this study ignites a fervent call for further investigation into the potential influence of names on criminal conduct. As we plunge into the depths of this scorching correlation, we are poised to unravel the enigmatic ties between nomenclature and nefarious acts, bearing witness to the captivating dance of data and the fiery allure of statistical inquiry.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of data spanning from 1985 to 2022 unveiled a striking correlation between the popularity of the first name "Jarred" and the incidence of arson in Rhode Island, illuminating a scorching correlation coefficient of 0.9564808. The r-squared value of 0.9148556 further corroborates the robustness of this relationship, highlighting the remarkable explanatory power encapsulated within this statistical inferno. With a p-value less than 0.01, the findings provide compelling evidence for a significant association, akin to a spark igniting a tinderbox of interest within the scientific community.

Figure 1 depicts a scatterplot visually capturing the incendiary correlation between the prevalence of the name "Jarred" and the frequency of arson occurrences in Rhode Island, akin to a fiery tango of data points. The inferno of statistical inference conjured by this symbiotic relationship blazes a trail for further exploration into the obscure intersection of nomenclature and criminal inclinations.

While the exact causal mechanisms underpinning this correlation remain shrouded in enigma, the results evoke a sense of intense curiosity and intrigue, akin to a mysterious flicker dancing at the periphery of scientific understanding. The illumination of this statistical bonfire engenders a fervent call for continued scrutiny and investigation, stoking the flames of inquiry into the potential impact of names on criminal behavior.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

[[LITERATURE REVIEW]]
The authors find that, despite the unconventional nature of our inquiry, the nexus between the prevalence of the first name "Jarred" and the incidence of arson in Rhode Island has drawn parallels with other studies exploring the influence of nomenclature on behavior. In "The Name Game: Cultural Signifiers and Psychological Impact," Smith and Doe delve into the societal perceptions and psychological implications associated with individuals' names, shedding light on the multifaceted dimensions of nomenclature. Similarly, Jones' work, "Appellations and Actions: Untangling the Web of Name and Behavior," offers a nuanced exploration of the interplay between names and behavior, albeit within a broader context.
Transitioning from the realm of scholarly research, popular non-fiction books such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner have captivated audiences with their unconventional lens on causation and correlation, engaging readers in a discourse that resonates with our investigative approach. Furthermore, the curious intersection of human behavior and nomenclature has found its place in fictional literature, with works such as "The Name of the Rose" by Umberto Eco and "The Shadow of the Wind" by Carlos Ruiz Zafón inviting readers into enigmatic narratives that subtly intertwine names with elusive fates.
Inspiration can also be drawn from board games such as "Clue," where the search for culprits and motives mirrors our scholarly pursuit of untangling the enigmatic ties between the prevalence of the name "Jarred" and the occurrence of arson in Rhode Island. The whimsical intrigue of board game dynamics offers a lighthearted reflection of our more serious inquiry, nudging us to ponder whether certain names may harbor clues to clandestine propensities or if the correlation we observe is a mere roll of the dice in the game of statistical analysis.
As the embers of empirical curiosity continue to flicker, this review sets the stage for a deeper exploration of the incendiary links between names and criminal acts, punctuating our scholarly inquiry with a touch of playful contemplation amidst the somber backdrop of statistical investigation.

[[RESULTS]]
The analysis of data spanning from 1985 to 2022 unveiled a striking correlation between the popularity of the first name "Jarred" and the incidence of arson in Rhode Island, illuminating a scorching correlation coefficient of 0.9564808. The r-squared value of 0.9148556 further corroborates the robustness of this relationship, highlighting the remarkable explanatory power encapsulated within this statistical inferno. With a p-value less than 0.01, the findings provide compelling evidence for a significant association, akin to a spark igniting a tinderbox of interest within the scientific community.
Figure 1 depicts a scatterplot visually capturing the incendiary correlation between the prevalence of the name "Jarred" and the frequency of arson occurrences in Rhode Island, akin to a fiery tango of data points. The inferno of statistical inference conjured by this symbiotic relationship blazes a trail for further exploration into the obscure intersection of nomenclature and criminal inclinations.
While the exact causal mechanisms underpinning this correlation remain shrouded in enigma, the results evoke a sense of intense curiosity and intrigue, akin to a mysterious flicker dancing at the periphery of scientific understanding. The illumination of this statistical bonfire engenders a fervent call for continued scrutiny and investigation, stoking the flames of inquiry into the potential impact of names on criminal behavior.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The scorching correlation uncovered in this study between the prevalence of the first name "Jarred" and the incidence of arson in Rhode Island burns brightly in the annals of empirical discovery. The results of this investigation, sizzling with statistical significance, lend credence to the prior research that has explored the fascinating interplay between nomenclature and behavior.

Drawing parallels with the scholarly works of Smith and Doe in "The Name Game: Cultural Signifiers and Psychological Impact" and Jones' "Appellations and Actions: Untangling the Web of Name and Behavior," our study ignites a fiery discourse on the multifaceted dimensions of names. Just as Levitt and Dubner's "Freakonomics" captivated audiences with unconventional causation analyses, our findings spark a conversation that may kindle a blaze of further inquiry into the potential influence of names on criminal proclivities.

The enigmatic ties between the popularity of the name "Jarred" and the occurrence of arson in Rhode Island, while seemingly peculiar, ripple across various spheres of human interaction and cognition, akin to the perplexing narratives of "The Name of the Rose" and "The Shadow of the Wind." Just as the game of "Clue" draws parallels to our scholarly pursuit, the interplay of names and behavior unfolds like a cerebral strategy in unraveling clandestine propensities.

The figures generated by our analysis, resembling a fiery tango of data points, cast a dramatic portrayal of the incendiary correlation between the name "Jarred" and arson occurrences in Rhode Island. The robust r-squared value further fans the flames of statistical inferno, underscoring the formidable explanatory power encapsulated within this scorching relationship.

The allure of this statistical bonfire beckons for continued scrutiny and investigation, akin to a mysterious flicker dancing at the periphery of scientific understanding. While we stand amidst the smoldering embers of empirical curiosity, the exact causal mechanisms underlying this empirical link continue to elude us, shrouding our inquiry in an enigmatic haze — like a phoenix rising from the ashes of statistical conjecture.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Jarred and Arson in Rhode Island. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

[[INTRDUCTION]]
The etymology of names has long been a topic of fascination, often inviting conjecture about the influence of nomenclature on personal characteristics and behavior. While popular culture and anecdotal evidence frequently offer colorful narratives about the impact of names on one's destiny, empirical research in this domain has been rather sparse. This study delves into the intriguing intersection of nomenclature and criminal behavior, focusing specifically on the relationship between the prevalence of the first name "Jarred" and the incidence of arson in the state of Rhode Island.
Perhaps it is serendipitous that the confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services has illuminated a compelling correlation, resembling a veritable firework display in the realm of statistical analysis. The scorching correlation coefficient of 0.9564808, coupled with a p-value less than 0.01, suggests a conspicuous association between the popularity of the name "Jarred" and the occurrence of arson in the Ocean State. The sheer heat emitted by this statistical relationship steers our inquiry into uncharted territory, where the flickering flames of curiosity are kindled.
It is akin to navigating through the smoky haze of empirical ambiguity, seeking to discern whether the fervor of names can indeed ignite criminal propensities or whether this incendiary correlation is merely a chance alignment of factors. Nevertheless, as we embark on this scholarly expedition, it is imperative to maintain a cautious stance, wary of falsely inferring causation from correlation. For if the mere mention of a name could stoke criminal proclivities, one might wonder whether other appellations harbor dormant potential for mischief, or whether certain names have a "spark" of criminality hidden within their syllables.
Amidst the smoldering embers of empirical inquiry, this study ignites a fervent call for further investigation into the potential influence of names on criminal conduct. As we plunge into the depths of this scorching correlation, we are poised to unravel the enigmatic ties between nomenclature and nefarious acts, bearing witness to the captivating dance of data and the fiery allure of statistical inquiry.

[[RESULTS]]
The analysis of data spanning from 1985 to 2022 unveiled a striking correlation between the popularity of the first name "Jarred" and the incidence of arson in Rhode Island, illuminating a scorching correlation coefficient of 0.9564808. The r-squared value of 0.9148556 further corroborates the robustness of this relationship, highlighting the remarkable explanatory power encapsulated within this statistical inferno. With a p-value less than 0.01, the findings provide compelling evidence for a significant association, akin to a spark igniting a tinderbox of interest within the scientific community.
Figure 1 depicts a scatterplot visually capturing the incendiary correlation between the prevalence of the name "Jarred" and the frequency of arson occurrences in Rhode Island, akin to a fiery tango of data points. The inferno of statistical inference conjured by this symbiotic relationship blazes a trail for further exploration into the obscure intersection of nomenclature and criminal inclinations.
While the exact causal mechanisms underpinning this correlation remain shrouded in enigma, the results evoke a sense of intense curiosity and intrigue, akin to a mysterious flicker dancing at the periphery of scientific understanding. The illumination of this statistical bonfire engenders a fervent call for continued scrutiny and investigation, stoking the flames of inquiry into the potential impact of names on criminal behavior.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our findings illuminate a compelling correlation between the popularity of the first name "Jarred" and the incidence of arson in Rhode Island. The scorching correlation coefficient, reminiscent of a sizzling barbeque, has sparked intense curiosity and garnered widespread attention within the academic community. While the exact reasons behind this association remain as elusive as a flickering campfire in the night, the statistical inferno we have uncovered certainly ignites the flames of further inquiry.

The implications of this research are akin to a smoke detector sounding an alarm, prompting us to reconsider the potential influence of nomenclature on criminal behavior. It seems that the mere mention of a name could fan the flames of criminal proclivities, raising the titillating possibility that other names may harbor hidden sparks of mischief. It's as if each name carries its own set of combustible characteristics, waiting to erupt into statistical conflagration.

As we extinguish our analysis, it is evident that the fiery allure of statistical inquiry beckons us to delve deeper into the enigmatic ties between nomenclature and nefarious acts. It is in the spirit of scientific exploration that we recommend further investigation into this incendiary correlation, but perhaps it's time to let this particular line of research cool off. After all, there's no need to keep fanning the flames – our findings have already set the research world on fire.


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 Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Forensic Psychology and Criminology


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 Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Sociolinguistic Arson Studies


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 Heat of the Moment: Exploring the Ignition of Arson in Rhode Island with the Popularity of the Name Jarred with an abstract of This study examines the relationship between the popularity of the first name "Jarred" and the occurrence of arson in the state of Rhode Island. Digging deep into the US Social Security Administration and FBI Criminal Justice Information Services data from 1985 to 2022, a striking correlation coefficient of 0.9564808 was unearthed, with p < 0.01, signifying a statistically significant correlation. While the causation remains elusive, the results certainly set the research world ablaze with curiosity. What's in a name, or rather, what's in a "Jarred"? This paper highlights the need for further investigation into the potential fiery influence of names on criminal behavior.

ChatGPT:

name popularity, arson, Rhode Island, "Jarred", correlation coefficient, Social Security Administration data, FBI Criminal Justice Information Services data

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



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Data details

Popularity of the first name Jarred
Detailed data title: Babies of all sexes born in the US named Jarred
Source: US Social Security Administration
See what else correlates with Popularity of the first name Jarred

Arson in Rhode Island
Detailed data title: The arson rate per 100,000 residents in Rhode Island
Source: FBI Criminal Justice Information Services
See what else correlates with Arson in Rhode Island

Correlation r = 0.9564808 (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 = 0.9148556 (Coefficient of determination)
This means 91.5% of the change in the one variable (i.e., Arson in Rhode Island) is predictable based on the change in the other (i.e., Popularity of the first name Jarred) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.6E-21. 0.0000000000000000000076182058
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 0.96 in 7.6E-19% of random cases. Said differently, if you correlated 131,264,503,250,883,559,424 random variables You don't actually need 131 quintillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 37 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 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.

[ 0.92, 0.98 ] 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.
19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Jarred (Babies born)44846148055260756448650356250649346748954256149937526720415112812599806258496961554346332935192011
Arson in Rhode Island (Arson rate)66.555.749.561.667.165.970.367.761.759.879.46764.158.464.565.966.656.842.727.920.319.321.519.422.122.817.817.316.515.116.313.212.37.78.211.38.77.8




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([448,461,480,552,607,564,486,503,562,506,493,467,489,542,561,499,375,267,204,151,128,125,99,80,62,58,49,69,61,55,43,46,33,29,35,19,20,11,])
array_2 = np.array([66.5,55.7,49.5,61.6,67.1,65.9,70.3,67.7,61.7,59.8,79.4,67,64.1,58.4,64.5,65.9,66.6,56.8,42.7,27.9,20.3,19.3,21.5,19.4,22.1,22.8,17.8,17.3,16.5,15.1,16.3,13.2,12.3,7.7,8.2,11.3,8.7,7.8,])
array_1_name = "Popularity of the first name Jarred"
array_2_name = "Arson in Rhode Island"

# 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: 1215 · Black Variable ID: 2937 · Red Variable ID: 20068
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