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spurious scholar

Because if p < 0.05, why not publish?

Step 1: Gather a bunch of data. There are 25,156 variables in my database. The data ranges from the mundane (air pollution in Chicago) to the weird (Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion) to the super-niche (How clickbait-y Numberphile YouTube video titles are, as rated by an AI).
Step 2: Dredge that data to find random correlations between variables. "Dredging data" means taking one variable and correlating it against every other variable just to see what sticks. It's a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.

Fun fact: the chart used on the wikipedia page to demonstrate data dredging is also from me. I've been being naughty with data since 2014.

Step 3: Calculate the correlation coefficient, confidence interval, and p-value to see if the connection is statistically significant. "Statistically significant" is a misleading term. It sounds like it means "statistically significant" because, you know, those are the same two words. Unfortunately statistical significance is a technical term that means mumble mumble at least as extreme mumble mumble null hypothesis mumble mumble probability mumble mumble p-values.

You know what? Forget the technical definition. "Statistically significant" just means "someone did some fancy math."

I really did the fancy math below and you can check it by clicking on the "view detailed data" link under each paper. And these really do qualify as "statistically significant" in the technical sense. It's just that "statistically significant" does not mean the results are "significant."

Step 4: If it is, have a large language model draft a research paper.
Step 5: Remind everyone that these papers are AI-generated and are not real. Seriously, just pick one and read the lit review section. The silliness of the papers is an artifact of me (1) having fun and (2) acknowledging that realistic-looking AI-generated noise is a real concern for academic research (peer reviews in particular).

The papers could sound more realistic than they do, but I intentionally prompted the model to write papers that look real but sound silly.

Also: every page says "This paper is AI-generated" at the bottom and the first letters of the names of the authors always spell out C-H-A-T-G-P-T.

Step 6: ...publish:

How Cool Is That Video? The Connection Between AsapSCIENCE YouTube Titles and Psychiatry Populations in Colorado
The Journal of Internet Psychology and Mental Health
r=0.849 · 95% conf. int. [0.508,0.960] · r2=0.721 · p < 0.01
Generated Jan 2024 · View data details

Counting on the Clickbait: The Correlation Between Professional-Sounding MrBeast YouTube Video Titles and Secretarial Employment in New Mexico
The Journal of Digital Media Studies
r=0.975 · 95% conf. int. [0.902,0.994] · r2=0.950 · p < 0.01
Generated Jan 2024 · View data details

Simone Giertz's Provocative Video Titles and Iowa's Event Planner Delights: A Rhyming Correlation
The Journal of Witty Observations and Quirky Investigations
r=0.953 · 95% conf. int. [0.785,0.990] · r2=0.907 · p < 0.01
Generated Jan 2024 · View data details

Breath of Fresh Air: Correlating 11th Grade Student Numbers with Air Quality in Odessa, Texas
The Journal of Environmental Pedagogy
r=0.905 · 95% conf. int. [0.814,0.952] · r2=0.818 · p < 0.01
Generated Jan 2024 · View data details

Breath of Fresh Heir: Examining the Relationship Between Air Quality in Tallahassee and Google Searches for 'How to Make Baby'
The Journal of Quirky Environmental Research
r=0.932 · 95% conf. int. [0.833,0.973] · r2=0.868 · p < 0.01
Generated Jan 2024 · View data details

Peculiar Parallels: Probing the Link Between Pollution in Somerset and Propulsion in Former Czechoslovakia
The Journal of Ecological Quirks and Curiosities
r=0.844 · 95% conf. int. [0.524,0.955] · r2=0.713 · p < 0.01
Generated Jan 2024 · View data details

Air Pollution in Watertown, New York: A Romantic Connection with xkcd Comics
The Journal of Ecological Humor and Pop Culture Studies
r=0.806 · 95% conf. int. [0.531,0.927] · r2=0.650 · p < 0.01
Generated Jan 2024 · View data details

Air Bags and Ballots: Exploring the Inflated Relationship between Libertarian Votes and Automotive Recalls in Iowa
Journal of Quirky Interdisciplinary Studies
r=0.971 · 95% conf. int. [0.843,0.995] · r2=0.943 · p < 0.01
Generated Jan 2024 · View data details

The Emani Effect: How Emani-nating Names Influence Political Tides
The Journal of Linguistic Influence and Sociopolitical Dynamics
r=0.831 · 95% conf. int. [0.305,0.969] · r2=0.691 · p < 0.05
Generated Jan 2024 · View data details

Driving the Point Home: The Air Bag Issue and the Libertarian Vote in California
The Journal of Political Behavior and Automotive Safety
r=0.938 · 95% conf. int. [0.689,0.989] · r2=0.880 · p < 0.01
Generated Jan 2024 · View data details

Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020
Journal of Social Dynamics and Cultural Trends
r=0.971 · 95% conf. int. [0.842,0.995] · r2=0.942 · p < 0.01
Generated Jan 2024 · View data details

Maine Votes and Bahama Breezes: Uncovering the Surprising Link between Democrat Support and Fossil Fuel Use
The Journal of Political Ecotrends
r=0.972 · 95% conf. int. [0.894,0.993] · r2=0.946 · p < 0.01
Generated Jan 2024 · View data details

From Red to Read: The Interplay of Republican Votes in North Dakota and Customer Satisfaction with NYTimes.com
The Journal of Political Psychology and Online Behavior
r=0.978 · 95% conf. int. [0.808,0.998] · r2=0.957 · p < 0.01
Generated Jan 2024 · View data details

Breaking News: The Brake for Libertarians - An Empirical Study on the Correlation between Votes for the Libertarian Presidential Candidate in Rhode Island and Automotive Recalls for Parking Brake Issues
The Journal of Automotive Political Science
r=0.955 · 95% conf. int. [0.830,0.988] · r2=0.911 · p < 0.01
Generated Jan 2024 · View data details

From Vincennes to India: Clearing the Air on Biomass Power
Journal of Renewable Energy Studies
r=0.918 · 95% conf. int. [0.813,0.965] · r2=0.842 · p < 0.01
Generated Jan 2024 · View data details

The Curtain Call of Clean Air: A Visual and Performing Arts Master's Degree Connection to Air Quality in Bishop, California
Journal of Interdisciplinary Air Quality Research
r=0.878 · 95% conf. int. [0.555,0.971] · r2=0.771 · p < 0.01
Generated Jan 2024 · View data details

Smoke Signals: Investigating the Relationship Between Air Quality in Lynchburg, Virginia and Google Searches for 'Tummy Ache'
Journal of Clandestine Air Quality Research
r=0.924 · 95% conf. int. [0.810,0.971] · r2=0.854 · p < 0.01
Generated Jan 2024 · View data details

Shedding Light on Pollution: Examining the Solar Connection Between Rocky Mount, NC and Libya
The Journal of Ecological Connections
r=0.968 · 95% conf. int. [0.888,0.991] · r2=0.938 · p < 0.01
Generated Jan 2024 · View data details

Gangnam Air: A Study on the Correlation between Air Pollution in Deming, New Mexico and Google Searches for 'Gangnam Style'
Journal of Unusual Correlations
r=0.932 · 95% conf. int. [0.769,0.981] · r2=0.868 · p < 0.01
Generated Jan 2024 · View data details

The Air is a-Buzz: Exploring the Relationship Between Air Quality in Rocky Mount, North Carolina, and the Number of Active Magazines in the United States
The Journal of Atmospheric Anthropology
r=0.919 · 95% conf. int. [0.769,0.973] · r2=0.845 · p < 0.01
Generated Jan 2024 · View data details

Burning the Midnight Oil: Exploring the Relationship Between Air Pollution in Ottawa and Kerosene Consumption in Canada
The Journal of Environmental Epidemiology and Energy Consumption
r=0.840 · 95% conf. int. [0.680,0.924] · r2=0.706 · p < 0.01
Generated Jan 2024 · View data details

Toxic Toledo Air and Titanic Trend Searches: A Tale of Sorrow and Search History Tomorrow
International Journal of Environmental Psychology and Digital Sociology
r=0.868 · 95% conf. int. [0.653,0.953] · r2=0.753 · p < 0.01
Generated Jan 2024 · View data details

Air Quality in Arizona: Assessing the Affinity between Ambient Atmosphere and Instagram Inquiries
Journal of Ecological and Social Media Studies
r=0.804 · 95% conf. int. [0.454,0.939] · r2=0.646 · p < 0.01
Generated Jan 2024 · View data details

Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple
The Journal of Environmental Aesthetics and Fruit-Based Technology
r=0.807 · 95% conf. int. [0.621,0.907] · r2=0.651 · p < 0.01
Generated Jan 2024 · View data details

Sniffing Out Snoop Dog: The Link Between Berlin's Dirty Air and Google Searches for the Furry Rapper
The Journal of Unlikely Correlations
r=0.815 · 95% conf. int. [0.583,0.924] · r2=0.664 · p < 0.01
Generated Jan 2024 · View data details


Currently viewing 25 of 4,731 spurious research papers

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Why this works

  1. Data dredging: I have 25,156 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,824,336 correlation calculations! This is called “data dredging.” Fun fact: the chart used on the wikipedia page to demonstrate data dredging is also from me. I've been being naughty with data since 2014.
    Instead of starting with a hypothesis and testing it, I isntead tossed a bunch of data in a blender to see what correlations would 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 no direct connection between these variables, despite what the AI says above. 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.
    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. You will often see trend-lines form. 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 naive p-value calculation does not take this into account. You will calculate a lower chance of "randomly" achieving the result than represents reality.

    To be more specific: p-value tests are probability values, where you are calculating the probability of achieving a result at least as extreme as you found completely by chance. When calculating a p-value, you need to assert how many "degrees of freedom" your variable has. I count each year (minus one) as a "degree of freedom," but this is misleading for continuous variables.

    This kind of thing can creep up on you pretty easily when using p-values, which is why it's best to take it as "one of many" inputs that help you assess the results of your analysis.
  4. Outliers: Some datasets here have outliers which drag up the correlation. In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

    Because this page is automatically generated, I don't know whether any of the charts displayed on it have outliers. I'm just a footnote. ¯\_(ツ)_/¯
    I intentionally mishandeled outliers, which makes the correlation look extra strong.



Spurious Scholar was launched January 27, 2024. If you have feedback on it, I'd love to hear from you! Shoot me a note: feedback@tylervigen.com.


Project by Tyler Vigen
emailme@tylervigen.com · about · subscribe


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