🕷️ Crawler Inspector

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Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 84 (from laksa004)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa084.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html\')), getAhrefsUnparsedNoserviceFromURL(\'https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html","crawl_time":1776466297,"first_indexed_time":1721683925,"http_code":200,"src_unparsed":"com,nytimes!www,\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html s443","src_root_hash":"4566504020376537684","history_drop_reason":null,"meta_title":"Opinion | Which Country Will Win the Paris Olympics? Don’t Just Count Medals. - The New York Times","meta_descriptions":["Conventional ranking methods are flawed, but there’s a better way."],"attrs_boilerpipe_text":"Advertisement\nSKIP ADVERTISEMENT\nNo nation officially wins the Olympics, but that doesn’t stop journalists and others from trying to keep score by counting gold, silver and bronze medals. Unfortunately, the two main approaches are equally flawed. The raw medal count overly favors populous nations, while ranking nations by medals per capita overly favors small nations that win one, two or a few medals, possibly by fluke.\nThere is a better way to rank nations by their Olympic prowess. I was put in touch with the researchers who developed the concept by Pete Pfitzinger, a college classmate of mine who was the top American marathoner in the Olympics of 1984 and 1988.\nFirst, though, let me go into what’s wrong with the medals-per-capita approach, which certainly seems fair. The problem, as I said, is that it’s not reliable when it comes to the performance of very small nations. In the Tokyo Games held in 2021, for example, the medals-per-capita winner by far was San Marino, which somehow won three medals (two in trap shooting, one in wrestling) despite a population of only around 34,000. Behind it were Bermuda and Grenada, with one medal apiece.\nAs statisticians know, the smaller a sample is, the bigger its variance. People who ignore or don’t know about this statistical property can be badly misled. For example, rural counties dominate the list of counties with the highest kidney cancer rates, which seems like a good reason to rush funding to rural health authorities. But guess what — rural counties also dominate the list of counties with the\nlowest\nkidney cancer rates.\nSame goes in education. After researchers noticed that small schools dominated the list of best performers based on average student test scores, there was a flurry of interest in promoting small schools, and even breaking up big ones. But then statisticians pointed out that the very worst performing schools by average student scores were also mostly small ones. There’s simply a wider spread when samples are small. For more on this, I recommend\nthis excellent article\nin American Scientist by Howard Wainer, a past principal research scientist at the Educational Testing Service.\nThe better Olympic rating system I mentioned is more balanced, advantaging neither the biggest nor the smallest nations. It was created by Robert Duncan, an astrophysicist now retired from the University of Texas, and Andrew Parece, a vice president at Charles River Associates, a consulting firm in Boston. After I started corresponding with them, their paper on the matter, “Population-Adjusted National Rankings in the Olympics,” was\npublished\nin The Journal of Sports Analytics.\nThe Duncan-Parece model ranks countries according to how improbable their medal counts are if one assumes that all medal-winning nations have an equal propensity per capita for winning medals. Its measure of improbability is based on the so-called\nbinomial distribution formula\n, which is the one you would use to calculate the likelihood of flipping heads, say, 10 times in a row.\nApplying their method to the Tokyo Olympics, the top 10 countries in order were Australia, Britain, the Netherlands, New Zealand, Hungary, the United States, Italy, Japan, Cuba and Jamaica. In the 2016 Olympic Games in Rio de Janeiro, their top 10 were Britain, the United States, New Zealand, Australia, France, Denmark, Azerbaijan, Jamaica, Germany and the Netherlands.\nThe authors thank Pfitzinger, the Olympic marathoner, for identifying the problem with the conventional ranking methods and urging them to solve it. They acknowledge that “there exists no perfect and absolutely ‘correct’ way to do Olympic national ranking.”\nI asked Andrew Gelman, a statistics professor at Columbia and\nblogger\n, what he thinks of the Duncan-Parece model. “Good for them,” he said. He said theirs was a reasonable way, though not the only one, to strike a balance between big and small countries.\nSmall sample sizes are tricky to interpret no matter what ranking method one uses, Gelman added. For example, if a small country wins a surprisingly high number of Olympic medals, it might not match that performance in four or eight years. Or it might!\nThe Duncan-Parece model is good for ranking, as in the Olympic comparisons, but possibly not so much for diagnostics, as in kidney cancer and school test scores. “I think that for those problems there are clearer targets and it makes sense to attack the problems directly. The Olympics thing is different because there the goal is to rank, not to measure,” Gelman wrote.\nIf you want to see how nations fare in the Summer Games in Paris according to Duncan and Parece’s model, check out\nthis website\n.\nElsewhere: Minimum Wages in California\nCalifornia was\ntied\nwith Nevada as of June for the highest unemployment rate in the 50 states. California also has high minimum wages. Is there a connection? Two recent studies reached opposite conclusions. Beacon Economics, a Los Angeles-based forecaster that has received research support in the past from the California Restaurant Association, found that the increase in California’s unemployment was led by people under 25 and\nwrote\n, “Look no further than the state’s aggressive minimum wage mandates.” In contrast, a\nreport\nby four economists for the Washington Center for Equitable Growth, which receives support from nonprofit foundations, found that minimum wage increases in California and New York “did not cause disemployment effects” for fast-food workers in 36 big counties in California and New York.\nThe Equitable Growth researchers theorize that before the increase in minimum wages, fast-food restaurants were using their market power to suppress wages and that they absorbed the higher minimums partly by accepting slimmer profit margins. In an email, they wrote that the Beacon Economics study found correlation between higher wage floors and unemployment in California, but not causation. Christopher Thornberg, the founding partner of Beacon Economics, claimed that the authors of the Equitable Growth paper “started with the answer and tortured the data to get it to confess.” He added: “Mind you, I appreciate they will say the same about me!”\nQuote of the Day\n“The most fateful change that unfolded during the past three decades was not an increase in greed. It was the expansion of markets, and of market values, into spheres of life where they don’t belong.”\n— Michael Sandel, “What Money Can’t Buy: The Moral Limits of Markets” (2012)\nMore from the Peter Coy Newsletter\nPeter Coy\nA veteran business and economics columnist unpacks the biggest headlines. Sends two times a week.\nGet it in your inbox.\nRecent issues from this newsletter\nExplore our newsletters\nBuild your routine with some of our top newsletters or\nview them all here.\nStay up to date\nGet informed as important news breaks around the world.\nStart your day\nMake sense of the day’s news and ideas.\nUnwind\nCatch up on the biggest news, and wind down to end your day.\nExpert political analysis\nMaking sense of elections, politics and polling.\nGet clear-eyed analysis\nNews and insights for a warming world.\nWhat to watch\nDiscover TV and movie recommendations from critic Margaret Lyons and friends.\nImprove your well-being\nEssential news and guidance to live your healthiest life.\nYour questions answered\nExpert advice on life’s trickiest situations and moral dilemmas.\nAdvertisement\nSKIP ADVERTISEMENT","attrs_markdown":"[Skip to content](https:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html#site-content)[Skip to site index](https:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html#site-index)\n\nSearch & Section Navigation\n\nSection Navigation\n\nSearch\n\n[Log in](https:\/\/myaccount.nytimes.com\/auth\/login?response_type=cookie&client_id=vi&redirect_uri=https%3A%2F%2Fwww.nytimes.com%2Fsubscription%2Fonboarding-offer%3FcampaignId%3D7JFJX%26EXIT_URI%3Dhttps%253A%252F%252Fwww.nytimes.com%252F2024%252F07%252F22%252Fopinion%252Fparis-olympics-medals-winner.html&asset=masthead)\n\nFriday, April 17, 2026\n\n[Today’s Paper](https:\/\/www.nytimes.com\/section\/todayspaper)\n\n[Opinion](https:\/\/www.nytimes.com\/section\/opinion)\\|Which Country Will Win the Paris Olympics? Don’t Just Count Medals.\n\nhttps:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html\n\n- Share full article\n\nAdvertisement\n\n[SKIP ADVERTISEMENT](https:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html#after-top)\n\n[Subscriber-only NewsletterPeter Coy](https:\/\/www.nytimes.com\/newsletters\/signup\/PC)\n\n[Opinion](https:\/\/www.nytimes.com\/section\/opinion)\n\n# Which Country Will Win the Paris Olympics? Don’t Just Count Medals.\nJuly 22, 2024\n\n![An illustration depicting a red medal, on a blue ribbon, featuring a number of human figures in white silhouette.](https:\/\/static01.nyt.com\/images\/2024\/07\/22\/opinion\/22coy-final\/22coy-final-articleLarge-v2.jpg?quality=75&auto=webp&disable=upscale)\n\nCredit...Illustration by The New York Times; Images by Peter6666, and Pure Imagination, via Getty Images\n\n- Share full article\n\n[![Peter Coy](https:\/\/static01.nyt.com\/images\/2022\/02\/27\/opinion\/author-peter-coy-2\/Peter_Coy_Final-thumbLarge.png)](https:\/\/www.nytimes.com\/by\/peter-coy)\n\nBy [Peter Coy](https:\/\/www.nytimes.com\/by\/peter-coy)\n\nOpinion Writer\n\n[See more of our coverage in your search results.Encuentra más de nuestra cobertura en los resultados de búsqueda. Add The New York Times on GoogleAgrega The New York Times en Google](https:\/\/www.google.com\/preferences\/source?cs=0&hl=en&q=nytimes.com)\n\nNo nation officially wins the Olympics, but that doesn’t stop journalists and others from trying to keep score by counting gold, silver and bronze medals. Unfortunately, the two main approaches are equally flawed. The raw medal count overly favors populous nations, while ranking nations by medals per capita overly favors small nations that win one, two or a few medals, possibly by fluke.\n\nThere is a better way to rank nations by their Olympic prowess. I was put in touch with the researchers who developed the concept by Pete Pfitzinger, a college classmate of mine who was the top American marathoner in the Olympics of 1984 and 1988.\n\nFirst, though, let me go into what’s wrong with the medals-per-capita approach, which certainly seems fair. The problem, as I said, is that it’s not reliable when it comes to the performance of very small nations. In the Tokyo Games held in 2021, for example, the medals-per-capita winner by far was San Marino, which somehow won three medals (two in trap shooting, one in wrestling) despite a population of only around 34,000. Behind it were Bermuda and Grenada, with one medal apiece.\n\nAs statisticians know, the smaller a sample is, the bigger its variance. People who ignore or don’t know about this statistical property can be badly misled. For example, rural counties dominate the list of counties with the highest kidney cancer rates, which seems like a good reason to rush funding to rural health authorities. But guess what — rural counties also dominate the list of counties with the *lowest* kidney cancer rates.\n\nSame goes in education. After researchers noticed that small schools dominated the list of best performers based on average student test scores, there was a flurry of interest in promoting small schools, and even breaking up big ones. But then statisticians pointed out that the very worst performing schools by average student scores were also mostly small ones. There’s simply a wider spread when samples are small. For more on this, I recommend [this excellent article](https:\/\/www.americanscientist.org\/article\/the-most-dangerous-equation) in American Scientist by Howard Wainer, a past principal research scientist at the Educational Testing Service.\n\nThe better Olympic rating system I mentioned is more balanced, advantaging neither the biggest nor the smallest nations. It was created by Robert Duncan, an astrophysicist now retired from the University of Texas, and Andrew Parece, a vice president at Charles River Associates, a consulting firm in Boston. After I started corresponding with them, their paper on the matter, “Population-Adjusted National Rankings in the Olympics,” was [published](https:\/\/content.iospress.com\/articles\/journal-of-sports-analytics\/jsa240874) in The Journal of Sports Analytics.\n\nThe Duncan-Parece model ranks countries according to how improbable their medal counts are if one assumes that all medal-winning nations have an equal propensity per capita for winning medals. Its measure of improbability is based on the so-called [binomial distribution formula](https:\/\/byjus.com\/binomial-distribution-formula\/), which is the one you would use to calculate the likelihood of flipping heads, say, 10 times in a row.\n\nApplying their method to the Tokyo Olympics, the top 10 countries in order were Australia, Britain, the Netherlands, New Zealand, Hungary, the United States, Italy, Japan, Cuba and Jamaica. In the 2016 Olympic Games in Rio de Janeiro, their top 10 were Britain, the United States, New Zealand, Australia, France, Denmark, Azerbaijan, Jamaica, Germany and the Netherlands.\n\nThe authors thank Pfitzinger, the Olympic marathoner, for identifying the problem with the conventional ranking methods and urging them to solve it. They acknowledge that “there exists no perfect and absolutely ‘correct’ way to do Olympic national ranking.”\n\n## Editors’ Picks\n[![](https:\/\/static01.nyt.com\/images\/2026\/04\/14\/travel\/14trav-skynest-05\/14trav-skynest-05-thumbLarge.jpg)You’ve Heard of the Sky Couch. Get Ready for the Skynest.](https:\/\/www.nytimes.com\/2026\/04\/14\/travel\/air-new-zealand-skynest-economy-sleep-pods.html)\n\n[![](https:\/\/static01.nyt.com\/images\/2026\/03\/26\/well\/WELL-UPLIFTING-BOOKS-image\/WELL-UPLIFTING-BOOKS-image-thumbLarge.jpg)5 Books to Lift You Up During Life’s Hardest Times](https:\/\/www.nytimes.com\/2026\/04\/15\/well\/uplifting-books.html)\n\n[![](https:\/\/static01.nyt.com\/images\/2026\/04\/15\/multimedia\/15wheels-evs-top-lctw\/15wheels-evs-top-lctw-thumbLarge.jpg)11 Electric Cars Worth a Look With Gas Prices High](https:\/\/www.nytimes.com\/2026\/04\/15\/business\/electric-cars-evs-used-gas-prices.html)\n\nAdvertisement\n\n[SKIP ADVERTISEMENT](https:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html#after-pp_edpick)\n\nI asked Andrew Gelman, a statistics professor at Columbia and [blogger](https:\/\/statmodeling.stat.columbia.edu\/), what he thinks of the Duncan-Parece model. “Good for them,” he said. He said theirs was a reasonable way, though not the only one, to strike a balance between big and small countries.\n\nSmall sample sizes are tricky to interpret no matter what ranking method one uses, Gelman added. For example, if a small country wins a surprisingly high number of Olympic medals, it might not match that performance in four or eight years. Or it might\\!\n\nThe Duncan-Parece model is good for ranking, as in the Olympic comparisons, but possibly not so much for diagnostics, as in kidney cancer and school test scores. “I think that for those problems there are clearer targets and it makes sense to attack the problems directly. The Olympics thing is different because there the goal is to rank, not to measure,” Gelman wrote.\n\nIf you want to see how nations fare in the Summer Games in Paris according to Duncan and Parece’s model, check out [this website](https:\/\/www.olympicnationalrankings.com\/).\n***\n\n## Elsewhere: Minimum Wages in California\nCalifornia was [tied](https:\/\/www.bls.gov\/web\/laus\/laumstrk.htm) with Nevada as of June for the highest unemployment rate in the 50 states. California also has high minimum wages. Is there a connection? Two recent studies reached opposite conclusions. Beacon Economics, a Los Angeles-based forecaster that has received research support in the past from the California Restaurant Association, found that the increase in California’s unemployment was led by people under 25 and [wrote](https:\/\/indd.adobe.com\/view\/acb6c12e-ad99-4ede-85ed-ba9f927dc5d1?utm_source=Beacon+Economics&utm_medium=Whitepaper&utm_campaign=California%E2%80%99s+Minimum+Wage+And+The+Long-Run+Consequences+For+The+State%E2%80%99s+Youth), “Look no further than the state’s aggressive minimum wage mandates.” In contrast, a [report](https:\/\/equitablegrowth.org\/working-papers\/minimum-wage-effects-and-monopsony-explanations\/) by four economists for the Washington Center for Equitable Growth, which receives support from nonprofit foundations, found that minimum wage increases in California and New York “did not cause disemployment effects” for fast-food workers in 36 big counties in California and New York.\n\nThe Equitable Growth researchers theorize that before the increase in minimum wages, fast-food restaurants were using their market power to suppress wages and that they absorbed the higher minimums partly by accepting slimmer profit margins. In an email, they wrote that the Beacon Economics study found correlation between higher wage floors and unemployment in California, but not causation. Christopher Thornberg, the founding partner of Beacon Economics, claimed that the authors of the Equitable Growth paper “started with the answer and tortured the data to get it to confess.” He added: “Mind you, I appreciate they will say the same about me!”\n***\n## Quote of the Day\n“The most fateful change that unfolded during the past three decades was not an increase in greed. It was the expansion of markets, and of market values, into spheres of life where they don’t belong.”\n\n— Michael Sandel, “What Money Can’t Buy: The Moral Limits of Markets” (2012)\n\nPeter Coy is a writer for the Opinion section of The Times, covering economics and business. Email him at [coy-newsletter@nytimes.com](mailto:coy-newsletter@nytimes.com).  [@petercoy](https:\/\/twitter.com\/petercoy)\n\n- Share full article\n\n## More from the Peter Coy Newsletter\n![Peter Coy](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-OP-PeterCoy.png)\n\nPeter Coy\n\nA veteran business and economics columnist unpacks the biggest headlines. Sends two times a week. Get it in your inbox.\n\n## Recent issues from this newsletter\n[![recent issues](https:\/\/static01.nyt.com\/images\/2025\/01\/31\/opinion\/31coy-newsletter-image\/31coy-newsletter-image-mediumThreeByTwo252.jpg)Illustration by Sam Whitney\/The New York Times; source images by CSA Images\/Getty Images](https:\/\/www.nytimes.com\/2025\/01\/31\/opinion\/retirement-roth-conversion.html)\n\n[The Retirement Maneuver More People Should Be Making](https:\/\/www.nytimes.com\/2025\/01\/31\/opinion\/retirement-roth-conversion.html)\n\n[![recent issues](https:\/\/static01.nyt.com\/images\/2025\/01\/27\/opinion\/27coy-newsletter-image\/27coy-newsletter-image-mediumThreeByTwo252.jpg)Illustration by Sam Whitney\/The New York Times; source images by CSA Images\/Getty Images](https:\/\/www.nytimes.com\/2025\/01\/27\/opinion\/big-problem-paradox.html)\n\n[Why Common Problems Are Often Worse Than We Realize](https:\/\/www.nytimes.com\/2025\/01\/27\/opinion\/big-problem-paradox.html)\n\n[![recent issues](https:\/\/static01.nyt.com\/images\/2025\/01\/24\/opinion\/24coy-newsletter-image\/24coy-newsletter-image-mediumThreeByTwo252.jpg)Illustration by Sam Whitney\/The New York Times; source photograph by EPA, via Shutterstock](https:\/\/www.nytimes.com\/2025\/01\/24\/opinion\/trump-bond-market-stocks.html)\n\n[Trump’s Greatest Resistance Could Come From Wall Street](https:\/\/www.nytimes.com\/2025\/01\/24\/opinion\/trump-bond-market-stocks.html)\n\n[![recent issues](https:\/\/static01.nyt.com\/images\/2025\/01\/23\/opinion\/20coy-newsletter-image\/20coy-newsletter-image-mediumThreeByTwo252.jpg)Illustration by Sam Whitney\/The New York Times; source images by CSA Images\/Getty Images](https:\/\/www.nytimes.com\/2025\/01\/20\/opinion\/trump-tariffs-trade.html)\n\n[The Debate Over Trump’s Favorite Word Needs a Reset](https:\/\/www.nytimes.com\/2025\/01\/20\/opinion\/trump-tariffs-trade.html)\n\n[![recent issues](https:\/\/static01.nyt.com\/images\/2025\/01\/17\/opinion\/17coy-newsletter-image\/17coy-newsletter-image-mediumThreeByTwo252.jpg)Illustration by Sam Whitney\/The New York Times; source images by mubai, Juniperocity and CSA Images\/Getty Images](https:\/\/www.nytimes.com\/2025\/01\/17\/opinion\/social-capital-loneliness.html)\n\n[Economics Has a Name for the Costs of Loneliness](https:\/\/www.nytimes.com\/2025\/01\/17\/opinion\/social-capital-loneliness.html)\n\n## Explore our newsletters\n### Build your routine with some of our top newsletters or [view them all here.](https:\/\/www.nytimes.com\/newsletters)\nStay up to date\n\nGet informed as important news breaks around the world.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-BreakingNews-Icon-500px.jpg)\n\nAs Needed\n\nBreaking News\n\n[See the latest](https:\/\/static.nytimes.com\/email-content\/NA_sample.html)\n\nStart your day\n\nMake sense of the day’s news and 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Unfortunately, the two main approaches are equally flawed. The raw medal count overly favors populous nations, while ranking nations by medals per capita overly favors small nations that win one, two or a few medals, possibly by fluke.\n\nThere is a better way to rank nations by their Olympic prowess. I was put in touch with the researchers who developed the concept by Pete Pfitzinger, a college classmate of mine who was the top American marathoner in the Olympics of 1984 and 1988.\n\nFirst, though, let me go into what’s wrong with the medals-per-capita approach, which certainly seems fair. The problem, as I said, is that it’s not reliable when it comes to the performance of very small nations. In the Tokyo Games held in 2021, for example, the medals-per-capita winner by far was San Marino, which somehow won three medals (two in trap shooting, one in wrestling) despite a population of only around 34,000. Behind it were Bermuda and Grenada, with one medal apiece.\n\nAs statisticians know, the smaller a sample is, the bigger its variance. People who ignore or don’t know about this statistical property can be badly misled. For example, rural counties dominate the list of counties with the highest kidney cancer rates, which seems like a good reason to rush funding to rural health authorities. But guess what — rural counties also dominate the list of counties with the *lowest* kidney cancer rates.\n\nSame goes in education. After researchers noticed that small schools dominated the list of best performers based on average student test scores, there was a flurry of interest in promoting small schools, and even breaking up big ones. But then statisticians pointed out that the very worst performing schools by average student scores were also mostly small ones. There’s simply a wider spread when samples are small. For more on this, I recommend [this excellent article](https:\/\/www.americanscientist.org\/article\/the-most-dangerous-equation) in American Scientist by Howard Wainer, a past principal research scientist at the Educational Testing Service.\n\nThe better Olympic rating system I mentioned is more balanced, advantaging neither the biggest nor the smallest nations. It was created by Robert Duncan, an astrophysicist now retired from the University of Texas, and Andrew Parece, a vice president at Charles River Associates, a consulting firm in Boston. After I started corresponding with them, their paper on the matter, “Population-Adjusted National Rankings in the Olympics,” was [published](https:\/\/content.iospress.com\/articles\/journal-of-sports-analytics\/jsa240874) in The Journal of Sports Analytics.\n\nThe Duncan-Parece model ranks countries according to how improbable their medal counts are if one assumes that all medal-winning nations have an equal propensity per capita for winning medals. Its measure of improbability is based on the so-called [binomial distribution formula](https:\/\/byjus.com\/binomial-distribution-formula\/), which is the one you would use to calculate the likelihood of flipping heads, say, 10 times in a row.\n\nApplying their method to the Tokyo Olympics, the top 10 countries in order were Australia, Britain, the Netherlands, New Zealand, Hungary, the United States, Italy, Japan, Cuba and Jamaica. In the 2016 Olympic Games in Rio de Janeiro, their top 10 were Britain, the United States, New Zealand, Australia, France, Denmark, Azerbaijan, Jamaica, Germany and the Netherlands.\n\nThe authors thank Pfitzinger, the Olympic marathoner, for identifying the problem with the conventional ranking methods and urging them to solve it. They acknowledge that “there exists no perfect and absolutely ‘correct’ way to do Olympic national ranking.”\n\nI asked Andrew Gelman, a statistics professor at Columbia and [blogger](https:\/\/statmodeling.stat.columbia.edu\/), what he thinks of the Duncan-Parece model. “Good for them,” he said. He said theirs was a reasonable way, though not the only one, to strike a balance between big and small countries.\n\nSmall sample sizes are tricky to interpret no matter what ranking method one uses, Gelman added. For example, if a small country wins a surprisingly high number of Olympic medals, it might not match that performance in four or eight years. Or it might\\!\n\nThe Duncan-Parece model is good for ranking, as in the Olympic comparisons, but possibly not so much for diagnostics, as in kidney cancer and school test scores. “I think that for those problems there are clearer targets and it makes sense to attack the problems directly. The Olympics thing is different because there the goal is to rank, not to measure,” Gelman wrote.\n\nIf you want to see how nations fare in the Summer Games in Paris according to Duncan and Parece’s model, check out [this website](https:\/\/www.olympicnationalrankings.com\/).\n***\n\n## Elsewhere: Minimum Wages in California\nCalifornia was [tied](https:\/\/www.bls.gov\/web\/laus\/laumstrk.htm) with Nevada as of June for the highest unemployment rate in the 50 states. California also has high minimum wages. Is there a connection? Two recent studies reached opposite conclusions. Beacon Economics, a Los Angeles-based forecaster that has received research support in the past from the California Restaurant Association, found that the increase in California’s unemployment was led by people under 25 and [wrote](https:\/\/indd.adobe.com\/view\/acb6c12e-ad99-4ede-85ed-ba9f927dc5d1?utm_source=Beacon+Economics&utm_medium=Whitepaper&utm_campaign=California%E2%80%99s+Minimum+Wage+And+The+Long-Run+Consequences+For+The+State%E2%80%99s+Youth), “Look no further than the state’s aggressive minimum wage mandates.” In contrast, a [report](https:\/\/equitablegrowth.org\/working-papers\/minimum-wage-effects-and-monopsony-explanations\/) by four economists for the Washington Center for Equitable Growth, which receives support from nonprofit foundations, found that minimum wage increases in California and New York “did not cause disemployment effects” for fast-food workers in 36 big counties in California and New York.\n\nThe Equitable Growth researchers theorize that before the increase in minimum wages, fast-food restaurants were using their market power to suppress wages and that they absorbed the higher minimums partly by accepting slimmer profit margins. In an email, they wrote that the Beacon Economics study found correlation between higher wage floors and unemployment in California, but not causation. Christopher Thornberg, the founding partner of Beacon Economics, claimed that the authors of the Equitable Growth paper “started with the answer and tortured the data to get it to confess.” He added: “Mind you, I appreciate they will say the same about me!”\n***\n## Quote of the Day\n“The most fateful change that unfolded during the past three decades was not an increase in greed. It was the expansion of markets, and of market values, into spheres of life where they don’t belong.”\n\n— Michael Sandel, “What Money Can’t Buy: The Moral Limits of Markets” (2012)\n\n## More from the Peter Coy Newsletter\n![Peter Coy](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-OP-PeterCoy.png)\n\nPeter Coy\n\nA veteran business and economics columnist unpacks the biggest headlines. Sends two times a week. Get it in your inbox.\n## Recent issues from this newsletter\n## Explore our newsletters\n### Build your routine with some of our top newsletters or [view them all here.](https:\/\/www.nytimes.com\/newsletters)\nStay up to date\n\nGet informed as important news breaks around the world.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-BreakingNews-Icon-500px.jpg)\n\nStart your day\n\nMake sense of the day’s news and ideas.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-TheMorning-Icon-500px.jpg)\n\nUnwind\n\nCatch up on the biggest news, and wind down to end your day.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-TheEvening-Icon.jpg)\n\nExpert political analysis\n\nMaking sense of elections, politics and polling.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/Sub_Only_Icons\/NYT-TheTilt-FN.jpg)\n\nGet clear-eyed analysis\n\nNews and insights for a warming world.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-ClimateForward-Icon-500px.jpg)\n\nWhat to watch\n\nDiscover TV and movie recommendations from critic Margaret Lyons and friends.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-SONL-Watching-Icon-500px.jpg)\n\nImprove your well-being\n\nEssential news and guidance to live your healthiest life.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-SONL-Well-Icon-500px.jpg)\n\nYour questions answered\n\nExpert advice on life’s trickiest situations and moral dilemmas.\n\n![Newsletter thumbnail](https:\/\/static.nytimes.com\/email-images\/NYT-Newsletters-SONL-TheEthicist-Icon-500px.jpg)\n\nAdvertisement\n\n[SKIP ADVERTISEMENT](https:\/\/www.nytimes.com\/2024\/07\/22\/opinion\/paris-olympics-medals-winner.html#after-bottom)","meta_canonical":null}

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Boilerpipe Text	Advertisement SKIP ADVERTISEMENT No nation officially wins the Olympics, but that doesn’t stop journalists and others from trying to keep score by counting gold, silver and bronze medals. Unfortunately, the two main approaches are equally flawed. The raw medal count overly favors populous nations, while ranking nations by medals per capita overly favors small nations that win one, two or a few medals, possibly by fluke. There is a better way to rank nations by their Olympic prowess. I was put in touch with the researchers who developed the concept by Pete Pfitzinger, a college classmate of mine who was the top American marathoner in the Olympics of 1984 and 1988. First, though, let me go into what’s wrong with the medals-per-capita approach, which certainly seems fair. The problem, as I said, is that it’s not reliable when it comes to the performance of very small nations. In the Tokyo Games held in 2021, for example, the medals-per-capita winner by far was San Marino, which somehow won three medals (two in trap shooting, one in wrestling) despite a population of only around 34,000. Behind it were Bermuda and Grenada, with one medal apiece. As statisticians know, the smaller a sample is, the bigger its variance. People who ignore or don’t know about this statistical property can be badly misled. For example, rural counties dominate the list of counties with the highest kidney cancer rates, which seems like a good reason to rush funding to rural health authorities. But guess what — rural counties also dominate the list of counties with the lowest kidney cancer rates. Same goes in education. After researchers noticed that small schools dominated the list of best performers based on average student test scores, there was a flurry of interest in promoting small schools, and even breaking up big ones. But then statisticians pointed out that the very worst performing schools by average student scores were also mostly small ones. There’s simply a wider spread when samples are small. For more on this, I recommend this excellent article in American Scientist by Howard Wainer, a past principal research scientist at the Educational Testing Service. The better Olympic rating system I mentioned is more balanced, advantaging neither the biggest nor the smallest nations. It was created by Robert Duncan, an astrophysicist now retired from the University of Texas, and Andrew Parece, a vice president at Charles River Associates, a consulting firm in Boston. After I started corresponding with them, their paper on the matter, “Population-Adjusted National Rankings in the Olympics,” was published in The Journal of Sports Analytics. The Duncan-Parece model ranks countries according to how improbable their medal counts are if one assumes that all medal-winning nations have an equal propensity per capita for winning medals. Its measure of improbability is based on the so-called binomial distribution formula , which is the one you would use to calculate the likelihood of flipping heads, say, 10 times in a row. Applying their method to the Tokyo Olympics, the top 10 countries in order were Australia, Britain, the Netherlands, New Zealand, Hungary, the United States, Italy, Japan, Cuba and Jamaica. In the 2016 Olympic Games in Rio de Janeiro, their top 10 were Britain, the United States, New Zealand, Australia, France, Denmark, Azerbaijan, Jamaica, Germany and the Netherlands. The authors thank Pfitzinger, the Olympic marathoner, for identifying the problem with the conventional ranking methods and urging them to solve it. They acknowledge that “there exists no perfect and absolutely ‘correct’ way to do Olympic national ranking.” I asked Andrew Gelman, a statistics professor at Columbia and blogger , what he thinks of the Duncan-Parece model. “Good for them,” he said. He said theirs was a reasonable way, though not the only one, to strike a balance between big and small countries. Small sample sizes are tricky to interpret no matter what ranking method one uses, Gelman added. For example, if a small country wins a surprisingly high number of Olympic medals, it might not match that performance in four or eight years. Or it might! The Duncan-Parece model is good for ranking, as in the Olympic comparisons, but possibly not so much for diagnostics, as in kidney cancer and school test scores. “I think that for those problems there are clearer targets and it makes sense to attack the problems directly. The Olympics thing is different because there the goal is to rank, not to measure,” Gelman wrote. If you want to see how nations fare in the Summer Games in Paris according to Duncan and Parece’s model, check out this website . Elsewhere: Minimum Wages in California California was tied with Nevada as of June for the highest unemployment rate in the 50 states. California also has high minimum wages. Is there a connection? Two recent studies reached opposite conclusions. Beacon Economics, a Los Angeles-based forecaster that has received research support in the past from the California Restaurant Association, found that the increase in California’s unemployment was led by people under 25 and wrote , “Look no further than the state’s aggressive minimum wage mandates.” In contrast, a report by four economists for the Washington Center for Equitable Growth, which receives support from nonprofit foundations, found that minimum wage increases in California and New York “did not cause disemployment effects” for fast-food workers in 36 big counties in California and New York. The Equitable Growth researchers theorize that before the increase in minimum wages, fast-food restaurants were using their market power to suppress wages and that they absorbed the higher minimums partly by accepting slimmer profit margins. In an email, they wrote that the Beacon Economics study found correlation between higher wage floors and unemployment in California, but not causation. Christopher Thornberg, the founding partner of Beacon Economics, claimed that the authors of the Equitable Growth paper “started with the answer and tortured the data to get it to confess.” He added: “Mind you, I appreciate they will say the same about me!” Quote of the Day “The most fateful change that unfolded during the past three decades was not an increase in greed. It was the expansion of markets, and of market values, into spheres of life where they don’t belong.” — Michael Sandel, “What Money Can’t Buy: The Moral Limits of Markets” (2012) More from the Peter Coy Newsletter Peter Coy A veteran business and economics columnist unpacks the biggest headlines. Sends two times a week. Get it in your inbox. Recent issues from this newsletter Explore our newsletters Build your routine with some of our top newsletters or view them all here. Stay up to date Get informed as important news breaks around the world. Start your day Make sense of the day’s news and ideas. Unwind Catch up on the biggest news, and wind down to end your day. Expert political analysis Making sense of elections, politics and polling. Get clear-eyed analysis News and insights for a warming world. What to watch Discover TV and movie recommendations from critic Margaret Lyons and friends. Improve your well-being Essential news and guidance to live your healthiest life. 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Markdown	[Skip to content](https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html#site-content)[Skip to site index](https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html#site-index) Search & Section Navigation Section Navigation Search [Log in](https://myaccount.nytimes.com/auth/login?response_type=cookie&client_id=vi&redirect_uri=https%3A%2F%2Fwww.nytimes.com%2Fsubscription%2Fonboarding-offer%3FcampaignId%3D7JFJX%26EXIT_URI%3Dhttps%253A%252F%252Fwww.nytimes.com%252F2024%252F07%252F22%252Fopinion%252Fparis-olympics-medals-winner.html&asset=masthead) Friday, April 17, 2026 [Today’s Paper](https://www.nytimes.com/section/todayspaper) [Opinion](https://www.nytimes.com/section/opinion)\\|Which Country Will Win the Paris Olympics? Don’t Just Count Medals. https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html - Share full article Advertisement [SKIP ADVERTISEMENT](https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html#after-top) [Subscriber-only NewsletterPeter Coy](https://www.nytimes.com/newsletters/signup/PC) [Opinion](https://www.nytimes.com/section/opinion) # Which Country Will Win the Paris Olympics? Don’t Just Count Medals. July 22, 2024 ![An illustration depicting a red medal, on a blue ribbon, featuring a number of human figures in white silhouette.](https://static01.nyt.com/images/2024/07/22/opinion/22coy-final/22coy-final-articleLarge-v2.jpg?quality=75&auto=webp&disable=upscale) Credit...Illustration by The New York Times; Images by Peter6666, and Pure Imagination, via Getty Images - Share full article [![Peter Coy](https://static01.nyt.com/images/2022/02/27/opinion/author-peter-coy-2/Peter_Coy_Final-thumbLarge.png)](https://www.nytimes.com/by/peter-coy) By [Peter Coy](https://www.nytimes.com/by/peter-coy) Opinion Writer [See more of our coverage in your search results.Encuentra más de nuestra cobertura en los resultados de búsqueda. Add The New York Times on GoogleAgrega The New York Times en Google](https://www.google.com/preferences/source?cs=0&hl=en&q=nytimes.com) No nation officially wins the Olympics, but that doesn’t stop journalists and others from trying to keep score by counting gold, silver and bronze medals. Unfortunately, the two main approaches are equally flawed. The raw medal count overly favors populous nations, while ranking nations by medals per capita overly favors small nations that win one, two or a few medals, possibly by fluke. There is a better way to rank nations by their Olympic prowess. I was put in touch with the researchers who developed the concept by Pete Pfitzinger, a college classmate of mine who was the top American marathoner in the Olympics of 1984 and 1988. First, though, let me go into what’s wrong with the medals-per-capita approach, which certainly seems fair. The problem, as I said, is that it’s not reliable when it comes to the performance of very small nations. In the Tokyo Games held in 2021, for example, the medals-per-capita winner by far was San Marino, which somehow won three medals (two in trap shooting, one in wrestling) despite a population of only around 34,000. Behind it were Bermuda and Grenada, with one medal apiece. As statisticians know, the smaller a sample is, the bigger its variance. People who ignore or don’t know about this statistical property can be badly misled. For example, rural counties dominate the list of counties with the highest kidney cancer rates, which seems like a good reason to rush funding to rural health authorities. But guess what — rural counties also dominate the list of counties with the lowest kidney cancer rates. Same goes in education. After researchers noticed that small schools dominated the list of best performers based on average student test scores, there was a flurry of interest in promoting small schools, and even breaking up big ones. But then statisticians pointed out that the very worst performing schools by average student scores were also mostly small ones. There’s simply a wider spread when samples are small. For more on this, I recommend [this excellent article](https://www.americanscientist.org/article/the-most-dangerous-equation) in American Scientist by Howard Wainer, a past principal research scientist at the Educational Testing Service. The better Olympic rating system I mentioned is more balanced, advantaging neither the biggest nor the smallest nations. It was created by Robert Duncan, an astrophysicist now retired from the University of Texas, and Andrew Parece, a vice president at Charles River Associates, a consulting firm in Boston. After I started corresponding with them, their paper on the matter, “Population-Adjusted National Rankings in the Olympics,” was [published](https://content.iospress.com/articles/journal-of-sports-analytics/jsa240874) in The Journal of Sports Analytics. The Duncan-Parece model ranks countries according to how improbable their medal counts are if one assumes that all medal-winning nations have an equal propensity per capita for winning medals. Its measure of improbability is based on the so-called [binomial distribution formula](https://byjus.com/binomial-distribution-formula/), which is the one you would use to calculate the likelihood of flipping heads, say, 10 times in a row. Applying their method to the Tokyo Olympics, the top 10 countries in order were Australia, Britain, the Netherlands, New Zealand, Hungary, the United States, Italy, Japan, Cuba and Jamaica. In the 2016 Olympic Games in Rio de Janeiro, their top 10 were Britain, the United States, New Zealand, Australia, France, Denmark, Azerbaijan, Jamaica, Germany and the Netherlands. The authors thank Pfitzinger, the Olympic marathoner, for identifying the problem with the conventional ranking methods and urging them to solve it. They acknowledge that “there exists no perfect and absolutely ‘correct’ way to do Olympic national ranking.” ## Editors’ Picks [![](https://static01.nyt.com/images/2026/04/14/travel/14trav-skynest-05/14trav-skynest-05-thumbLarge.jpg)You’ve Heard of the Sky Couch. Get Ready for the Skynest.](https://www.nytimes.com/2026/04/14/travel/air-new-zealand-skynest-economy-sleep-pods.html) [![](https://static01.nyt.com/images/2026/03/26/well/WELL-UPLIFTING-BOOKS-image/WELL-UPLIFTING-BOOKS-image-thumbLarge.jpg)5 Books to Lift You Up During Life’s Hardest Times](https://www.nytimes.com/2026/04/15/well/uplifting-books.html) [![](https://static01.nyt.com/images/2026/04/15/multimedia/15wheels-evs-top-lctw/15wheels-evs-top-lctw-thumbLarge.jpg)11 Electric Cars Worth a Look With Gas Prices High](https://www.nytimes.com/2026/04/15/business/electric-cars-evs-used-gas-prices.html) Advertisement [SKIP ADVERTISEMENT](https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html#after-pp_edpick) I asked Andrew Gelman, a statistics professor at Columbia and [blogger](https://statmodeling.stat.columbia.edu/), what he thinks of the Duncan-Parece model. “Good for them,” he said. He said theirs was a reasonable way, though not the only one, to strike a balance between big and small countries. Small sample sizes are tricky to interpret no matter what ranking method one uses, Gelman added. For example, if a small country wins a surprisingly high number of Olympic medals, it might not match that performance in four or eight years. Or it might\! The Duncan-Parece model is good for ranking, as in the Olympic comparisons, but possibly not so much for diagnostics, as in kidney cancer and school test scores. “I think that for those problems there are clearer targets and it makes sense to attack the problems directly. The Olympics thing is different because there the goal is to rank, not to measure,” Gelman wrote. If you want to see how nations fare in the Summer Games in Paris according to Duncan and Parece’s model, check out [this website](https://www.olympicnationalrankings.com/). * ## Elsewhere: Minimum Wages in California California was [tied](https://www.bls.gov/web/laus/laumstrk.htm) with Nevada as of June for the highest unemployment rate in the 50 states. California also has high minimum wages. Is there a connection? Two recent studies reached opposite conclusions. Beacon Economics, a Los Angeles-based forecaster that has received research support in the past from the California Restaurant Association, found that the increase in California’s unemployment was led by people under 25 and [wrote](https://indd.adobe.com/view/acb6c12e-ad99-4ede-85ed-ba9f927dc5d1?utm_source=Beacon+Economics&utm_medium=Whitepaper&utm_campaign=California%E2%80%99s+Minimum+Wage+And+The+Long-Run+Consequences+For+The+State%E2%80%99s+Youth), “Look no further than the state’s aggressive minimum wage mandates.” In contrast, a [report](https://equitablegrowth.org/working-papers/minimum-wage-effects-and-monopsony-explanations/) by four economists for the Washington Center for Equitable Growth, which receives support from nonprofit foundations, found that minimum wage increases in California and New York “did not cause disemployment effects” for fast-food workers in 36 big counties in California and New York. The Equitable Growth researchers theorize that before the increase in minimum wages, fast-food restaurants were using their market power to suppress wages and that they absorbed the higher minimums partly by accepting slimmer profit margins. In an email, they wrote that the Beacon Economics study found correlation between higher wage floors and unemployment in California, but not causation. Christopher Thornberg, the founding partner of Beacon Economics, claimed that the authors of the Equitable Growth paper “started with the answer and tortured the data to get it to confess.” He added: “Mind you, I appreciate they will say the same about me!” * ## Quote of the Day “The most fateful change that unfolded during the past three decades was not an increase in greed. It was the expansion of markets, and of market values, into spheres of life where they don’t belong.” — Michael Sandel, “What Money Can’t Buy: The Moral Limits of Markets” (2012) Peter Coy is a writer for the Opinion section of The Times, covering economics and business. Email him at [coy-newsletter@nytimes.com](mailto:coy-newsletter@nytimes.com). [@petercoy](https://twitter.com/petercoy) - Share full article ## More from the Peter Coy Newsletter ![Peter Coy](https://static.nytimes.com/email-images/NYT-Newsletters-OP-PeterCoy.png) Peter Coy A veteran business and economics columnist unpacks the biggest headlines. Sends two times a week. 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Readable Markdown	Advertisement [SKIP ADVERTISEMENT](https://www.nytimes.com/2024/07/22/opinion/paris-olympics-medals-winner.html#after-top) No nation officially wins the Olympics, but that doesn’t stop journalists and others from trying to keep score by counting gold, silver and bronze medals. Unfortunately, the two main approaches are equally flawed. The raw medal count overly favors populous nations, while ranking nations by medals per capita overly favors small nations that win one, two or a few medals, possibly by fluke. There is a better way to rank nations by their Olympic prowess. I was put in touch with the researchers who developed the concept by Pete Pfitzinger, a college classmate of mine who was the top American marathoner in the Olympics of 1984 and 1988. First, though, let me go into what’s wrong with the medals-per-capita approach, which certainly seems fair. The problem, as I said, is that it’s not reliable when it comes to the performance of very small nations. In the Tokyo Games held in 2021, for example, the medals-per-capita winner by far was San Marino, which somehow won three medals (two in trap shooting, one in wrestling) despite a population of only around 34,000. Behind it were Bermuda and Grenada, with one medal apiece. As statisticians know, the smaller a sample is, the bigger its variance. People who ignore or don’t know about this statistical property can be badly misled. For example, rural counties dominate the list of counties with the highest kidney cancer rates, which seems like a good reason to rush funding to rural health authorities. But guess what — rural counties also dominate the list of counties with the lowest kidney cancer rates. Same goes in education. After researchers noticed that small schools dominated the list of best performers based on average student test scores, there was a flurry of interest in promoting small schools, and even breaking up big ones. But then statisticians pointed out that the very worst performing schools by average student scores were also mostly small ones. There’s simply a wider spread when samples are small. For more on this, I recommend [this excellent article](https://www.americanscientist.org/article/the-most-dangerous-equation) in American Scientist by Howard Wainer, a past principal research scientist at the Educational Testing Service. The better Olympic rating system I mentioned is more balanced, advantaging neither the biggest nor the smallest nations. It was created by Robert Duncan, an astrophysicist now retired from the University of Texas, and Andrew Parece, a vice president at Charles River Associates, a consulting firm in Boston. After I started corresponding with them, their paper on the matter, “Population-Adjusted National Rankings in the Olympics,” was [published](https://content.iospress.com/articles/journal-of-sports-analytics/jsa240874) in The Journal of Sports Analytics. The Duncan-Parece model ranks countries according to how improbable their medal counts are if one assumes that all medal-winning nations have an equal propensity per capita for winning medals. Its measure of improbability is based on the so-called [binomial distribution formula](https://byjus.com/binomial-distribution-formula/), which is the one you would use to calculate the likelihood of flipping heads, say, 10 times in a row. Applying their method to the Tokyo Olympics, the top 10 countries in order were Australia, Britain, the Netherlands, New Zealand, Hungary, the United States, Italy, Japan, Cuba and Jamaica. In the 2016 Olympic Games in Rio de Janeiro, their top 10 were Britain, the United States, New Zealand, Australia, France, Denmark, Azerbaijan, Jamaica, Germany and the Netherlands. The authors thank Pfitzinger, the Olympic marathoner, for identifying the problem with the conventional ranking methods and urging them to solve it. They acknowledge that “there exists no perfect and absolutely ‘correct’ way to do Olympic national ranking.” I asked Andrew Gelman, a statistics professor at Columbia and [blogger](https://statmodeling.stat.columbia.edu/), what he thinks of the Duncan-Parece model. “Good for them,” he said. He said theirs was a reasonable way, though not the only one, to strike a balance between big and small countries. Small sample sizes are tricky to interpret no matter what ranking method one uses, Gelman added. For example, if a small country wins a surprisingly high number of Olympic medals, it might not match that performance in four or eight years. Or it might\! The Duncan-Parece model is good for ranking, as in the Olympic comparisons, but possibly not so much for diagnostics, as in kidney cancer and school test scores. “I think that for those problems there are clearer targets and it makes sense to attack the problems directly. The Olympics thing is different because there the goal is to rank, not to measure,” Gelman wrote. If you want to see how nations fare in the Summer Games in Paris according to Duncan and Parece’s model, check out [this website](https://www.olympicnationalrankings.com/). * ## Elsewhere: Minimum Wages in California California was [tied](https://www.bls.gov/web/laus/laumstrk.htm) with Nevada as of June for the highest unemployment rate in the 50 states. California also has high minimum wages. Is there a connection? Two recent studies reached opposite conclusions. Beacon Economics, a Los Angeles-based forecaster that has received research support in the past from the California Restaurant Association, found that the increase in California’s unemployment was led by people under 25 and [wrote](https://indd.adobe.com/view/acb6c12e-ad99-4ede-85ed-ba9f927dc5d1?utm_source=Beacon+Economics&utm_medium=Whitepaper&utm_campaign=California%E2%80%99s+Minimum+Wage+And+The+Long-Run+Consequences+For+The+State%E2%80%99s+Youth), “Look no further than the state’s aggressive minimum wage mandates.” In contrast, a [report](https://equitablegrowth.org/working-papers/minimum-wage-effects-and-monopsony-explanations/) by four economists for the Washington Center for Equitable Growth, which receives support from nonprofit foundations, found that minimum wage increases in California and New York “did not cause disemployment effects” for fast-food workers in 36 big counties in California and New York. The Equitable Growth researchers theorize that before the increase in minimum wages, fast-food restaurants were using their market power to suppress wages and that they absorbed the higher minimums partly by accepting slimmer profit margins. In an email, they wrote that the Beacon Economics study found correlation between higher wage floors and unemployment in California, but not causation. Christopher Thornberg, the founding partner of Beacon Economics, claimed that the authors of the Equitable Growth paper “started with the answer and tortured the data to get it to confess.” He added: “Mind you, I appreciate they will say the same about me!” * ## Quote of the Day “The most fateful change that unfolded during the past three decades was not an increase in greed. It was the expansion of markets, and of market values, into spheres of life where they don’t belong.” — Michael Sandel, “What Money Can’t Buy: The Moral Limits of Markets” (2012) ## More from the Peter Coy Newsletter ![Peter Coy](https://static.nytimes.com/email-images/NYT-Newsletters-OP-PeterCoy.png) Peter Coy A veteran business and economics columnist unpacks the biggest headlines. Sends two times a week. 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