Vysotsky was the author of the first "Serendipity" article in the Signpost in October 2021 and has now written fourteen editions of this column, more than half of them. The first article was about how Mr.Nostalgic had uploaded over 350,000 photographs to Commons including one that became a Serbian postage stamp. Mr.Nostalgic now has well over two million Commons uploads and Vysotsky continues with a much bigger story. – S

Several of these images are quite rare. There are in fact several dozen images from Leuven that are unique. There were no images of the depicted persons available in Wiki until the Leuven images came along. A dozen examples: images of the Belgian painter François-Antoine Bossuet, English diplomat Jerome Weston, 2nd Earl of Portland, Scottish politician Charles Hamilton, Lord Binning, Belgian writer Jan Ferguut, Belgian painter Jean Baptiste van Eycken, microbiologist Évariste Warlomont, Spanish theologian Tomaso Malvenda, astronomer Ernest Quetelet, liturgist Claude de Vert, French general Hyacinthe Despinoy, French painter Guillaume Boichot, mathematician Guillaume Le Blond, politician Georges Grimard and politician Arthur Meulemans – all unique images. These images are now available in Wikipedia thanks to Leuven Libraries and Mr.Nostalgic

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  Hyacinthe Despinoy
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  François-Antoine Bossuet
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  Gertrude of Saxony
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  Jan Ferguut
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  Georges Grimard

Usage of this collection is really good. Well over 1,000 images from Leuven are used 3,400 times in all Wikipedia language versions. Some images are used more than 10 times: Eliza Haywood, Louise Van den Plas, Richard Bentley and others. From the collection of glass slides, images of antiquities are popular: Tomb of Tutankhamun and statues of Venus but also College Hall in Philadelphia, der Breite Weg in Magdeburg, Deir el-Medina and the woolly mammoth. From the postcard collection some images stand out: the Italian Pavillion Brussels at the World Expo in 1910, and Château d'Elegem, Dilbeek.

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  Charles-Michel de l'Épée (sign language!)
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  Louise Van den Plas
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  Italian Pavillion Brussels
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  Eliza Haywood
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  Tomb of Tutankhamun

During the check of the descriptions and during the categorization of the images I also found a lot of incomplete and even some wrong descriptions ("Venili" instead of "Verdi"!). Remarks and suggestions are always sent to the librarians in Leuven. The descriptions of the original are then improved by staff from Leuven Libraries. As I was a librarian myself, I know how useful suggestions to improve metadata can be.

The following famous Belgians do have an article in the English, German or Chinese Wikipedia, but NOT in the Dutch – or French language Wikipedia. Composer Joseph Daussoigne-Méhul, painters Alfred Duriau & Henri Van Haelen, playwright Jan Frans Cammaert, writer Adolphe Mathieu, librettist Auguste Baron; botanists Martin Martens, Alexandre Louis Simon Lejeune, Richard Courtois, Eugène Coemans, Victor Grégoire; historians Antoine Schayes, Guillaume Arendt; medic Ernest Masoin, Liesbet Geris; entomologist (Luik) Henri-Maurice Gaëde, mathematician Alexis Timmermans, engineer Amaat Dumon, general Guillaume-Adolphe Nerenburger, nun Agnes Baliques and smartest Belgian of all time ("optimus doctissimusque Belgarum") Charles De Langhe. What are we waiting for?

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  Agnes Baliques
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  Jan Frans Cammaert
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  Charles De Langhe ("smartest Belgian of all time")
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  Auguste Baron
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  Amaat Dumon

What is the likelihood of having a biography on Wikipedia? How does it vary across the 10 major largest editions of Wikipedia? Does someone's country of birth affect the probability of having a biography? Which countries are overrepresented, and do different editions rank them differently? By combining demographic birth data from the United Nations World Population Prospects with biography counts by year and country of birth, this study offers new insights into geographical bias on Wikipedia.

Looking at raw biography counts in English Wikipedia, the United States leads with 337,763 biographies, followed by the United Kingdom (158,718) and Germany (69,204). India ranks 8th with 35,084 biographies, while the People's Republic of China ranks 14th with 18,648.^[1] These figures, however, reflect population size and historical documentation practices as much as anything else — to draw meaningful comparisons, they must be weighed against demographic data.

In 2022, I conducted an initial study comparing birth counts by department in metropolitan France, as provided by the French national statistical office, with the number of biographies sorted by department of birth.^[2] That was my first attempt to measure the likelihood of having a Wikipedia biography, though the scope was limited to France. I've been looking for a worldwide birth dataset to extend my analysis.

The United Nations World Population Prospects (WPP) turned out to be the perfect dataset for this purpose: it provides birth estimates by year and country going all the way back to 1950, enabling a global measure of the likelihood of having a Wikipedia biography.

I published the first version of my analysis for the French-language edition of Wikipedia last April.^[3] My analysis shows that microstates such as San Marino, Monaco, and Andorra lead the ranking, with more than 1 biography per 1,000 births, whereas major Asian countries such as China and India are at the very bottom of the rankings, with less than 1 per 100,000.

In this analysis, I propose to measure likelihood of having a biography on a global scale and at the country level for 18 different versions of Wikipedia. To my knowledge, this is the first study which computes the likelihood of having a biography at the country level.

For the purpose of this study, I've collected the Biographies vs Births dataset, a dataset which combines birth data from the World Population Prospect and Wikipedia biography counts from Wikidata.^[4]

More precisely, I use the estimated number of births (Births) to get number of births by country from 1950 to 2019 from 2024 edition of the World Population Prospects.^[5] Rather than tracking historical borders and former countries, the WPP uses current country definitions, which simplifies long-term cross-country comparisons.

I've collected number of biographies by country, and year of birth between 1950 and 2019 using Wikidata SPARQL queries.^[6] Data were collected on July 4, 2026. 18 editions of Wikipedia are included in the dataset: Arabic (ar), Czech (cs), German (de), English (en), Spanish (es), Persian (fa), French (fr), Hebrew (he), Italian (it), Japanese (ja), Korean (ko), Dutch (nl), Polish (pl), Russian (ru), Turkish (tr), Ukrainian (uk), Vietnamese (vi), and Chinese (zh) Wikipedia.

It is useful to keep in mind that the data could have some drawbacks. Some Wikipedia articles are not connected to a Wikidata item and some Wikidata items don't have precise information about birthdate and birthplace.

I estimate the likelihood or probability of having a biography in Wikipedia using the ratio of number of biographies and number of births over a time period. To keep the number of decimal places manageable, I multiply the ratio by one million. This gives the biographies per million births (bmb) ratio.

In this study, I focus on people born between 1950 and 1989. People born after 1990 have had less time to meet Wikipedia's notability criteria and are therefore systematically underrepresented in biography counts.

The biography per million births ratio is calculated both globally for each wiki and at the country/wiki granularity.

In this section, I first look at biographies per million births ratio at the global level, then I focus on the English Wikipedia, and finally I look at similarities and differences between the 18 editions of Wikipedia included in the study.

All results are produced in an Observable notebook.^[7]

Between 1950 and 1989, the World Population Prospects records a total of 4.7 billion births (4,726,859,446 births) across 216 countries. The biographies per million births ratio ranges from 5.5 for Vietnamese Wikipedia to 113.3 for the English edition. Nothing surprising here, this is just due to the difference in the number of biographical articles in the different editions of Wikipedia but this is useful to give some orders of magnitude of the probability of having a biography.

In this section, we focus on the English Wikipedia.

Globally, the results reveal stark disparities between countries: the likelihood of having a biography ranges from 7.5 per million births in Ethiopia to 13,340 in San Marino — meaning that while someone born in Ethiopia has roughly a 1-in-130,000 chance of being considered WP:NOTABLE enough to warrant a biography, someone born in San Marino has closer to a 1-in-75 chance. People born in San Marino are almost 2,000 times more likely to have a biography than those born in Ethiopia.

The five countries with the highest likelihood of having a biography in English Wikipedia are San Marino (13,339.6 biographies per million births), Andorra (8,593.8), Liechtenstein (7,922.5), Falkland Islands (6,082.7), and Iceland (5,302.5). The first four are very small countries with fewer than 15,000 births recorded over the 40-year period. Browsing the list of biographies by country show that local athletes could explain the relatively high number of biographies for those countries.^[8]

Globally, the top 20 includes a mix of very small countries such as Monaco, Faroe Islands, Cook Islands, Tonga, Cayman Islands, Antigua and Barbuda, Isle of Man, and Greenland, and small or relatively small countries such as Iceland, Luxembourg, Estonia, Norway, New Zealand, Ireland, and Sweden.

There is a decreasing relationship association between a country's demographic size, measured by the number of births between 1950 and 1990, and the probability of having a biography. Overall, a 1% increase in the number of births is associated with a 0.407% decrease of the probability of having a biography.

Figure 1 shows that English speaking countries such as New Zealand, Ireland, Canada, Great Britain, and the United States of America are far above the regression line, which means that their biographies per million births ratio is high relative to their birth count.

Figure 2 shows regional disparities of the biographies per million births ratio.

Western nations all have a high (above the 100) or very high (above 1,000) value of biographies per million births ratio: the United Kingdom has 1,361.3 biographies per million births, Canada 1,265.4, the United States (753.4), France (521.4), and Spain (482.8).

Latin American countries sit in the middle of the ranking. Argentina (279 biographies per million births) and Chile (232) exceed the global average, while Mexico (84), Brazil (80), and Peru (63) fall in the 50–100 range — well below the regional leaders but far from the bottom of the distribution.

Some Asian countries perform well above the regional average, including Japan (220 biographies per million births), South Korea (153), Malaysia (139), Taiwan (108), and Kazakhstan (102), all exceeding 100 biographies per million births. Many of the continent's most populous countries, however, rank near the bottom of the global distribution: India records just 16 biographies per million births, Indonesia 15, Myanmar 13, Vietnam 13, North Korea 13, Yemen 12, Bangladesh 10, and China 8.

Among large African countries, South Africa is the best ranked with 145.4 biographies per million births. Other African countries are below 100 biographies per million births. Ethiopia is the last one in the English Wikipedia with only 7.5 biographies per million births.

The biographies per million births ratio is highly correlated across the 18 editions of Wikipedia included in the studies. Overall, countries with a high biographies per million births ratio in one edition have a high biographies per million births ratio in another edition. All coefficients of correlation are greater than 0.7.

Since the correlation between the 18 editions of Wikipedia included in the study is very high, countries at the top of the ranking are often the same. San Marino is 1st in the English, German, French, Italian, Chinese and Polish editions, 2nd in the Spanish one, 7th in the Dutch one, 8th in the Japanese one, and 9th in the Persian edition. Andorra, Liechtenstein, Iceland, and Monaco are always in the top 10 and Nauru is in the top 10 9 times out of 10.

Though the rankings are globally similar across the 18 Wikipedia editions, there are also some remarkable differences.

In the Japanese edition, several Asian and Pacific countries rank notably higher than in the English edition: Japan climbs from 103rd to 3rd, the Republic of Korea from 116th to 54th, Taiwan from 129th to 77th, and the Democratic People's Republic of Korea from 205th to 134th. Pacific island nations also fare better, with Tuvalu rising from 19th to 4th, Tonga from 15th to 5th, and the Marshall Islands from 86st to 14th. Overall, Asian and Pacific countries are better represented in the Japanese edition than in the English one.

We find the same pattern for the Chinese edition: Taiwan climbs from 129th to 12th, China from 211th to 124th, the Republic of Korea from 116th to 43rd, Japan from 103rd to 26th, and the Democratic People's Republic of Korea from 205th to 129th. Tuvalu rising from 19th to 4th, and the Marshall Islands from 86th to 14th.

In the Persian edition, some Middle-Eastern countries are better represented than in the English edition: Qatar goes from 29th rank to 4th, Armenia from 91st to 6th, the United Arab Emirates from 50th to 8th, Bahrain from 75th to 16th, Kuwait from 97th to 33rd, and the Islamic Republic of Iran from 149th to 48th.

In the Arabic Wikipedia, Qatar jumps from 29th rank to 6th, United Arab Emirates from 50th to 10th, Bahrain from 75th to 17th, and the State of Palestine from 82nd to 21st.

The Hebrew edition has two noteworthy differences from the English one: Israël is 1st instead of 33rd and State of Palestine 3rd instead of 82nd.

In the Dutch edition, Tuvalu jumps from 23rd to 1st position, the Netherlands from 48th to 2nd, Belgium from 55th to 3rd, Suriname from 62nd to 5th, and Curaçao from 59th to 13th.

The Polish edition is very similar to the English edition. The main difference is the ranking of Poland (from 93rd to 10th).

In the Czech Wikipedia, again the main differences are, Czechia is 1st instead of 53rd and Slovakia 6th instead of 57th.

The Italian edition is also very close to the English one. Italy is ranked 8th instead of 78th.

In the French edition, countries with a French-speaking community are noticeably better represented. Switzerland rises from 35th to 10th, France from 68th to 14th, and Belgium from 55th to 13th. The effect extends beyond Europe: Gabon climbs from 113th to 68th, Tunisia from 130th to 76th, and Canada from 25th to 17th.

In the Spanish edition, Spanish-speaking countries are better represented than in the English one. Falkland Islands is 1st vs 4th, Spain 9th vs 72nd, Uruguay 10th vs 54th, Argentina 15th vs 95th, Chile 18th vs 101nd, etc.

For the German edition, we also find a bonus for German-speaking countries such as Germany (12th vs 71st), Switzerland (11th vs 35th) and Austria (8th vs 42nd). One noteworthy difference is Timor-Leste which jumps from 127th position in the English edition to the 44th position in the German one.

By combining demographic data with biography counts, this study sheds new light on Wikipedia's geographic biases and advances research on notability and representation.

The gap between the top and bottom of the distribution is striking, and the results appear highly consistent across the 18 Wikipedia editions included in the study.

A cluster of very small countries — San Marino, Monaco, Andorra, Liechtenstein, and Nauru — consistently rank at the top of the distribution, while populous Asian countries such as India and China remain at the bottom.

In addition to this study, I release the first version of the Biographies vs Births dataset. Researchers, journalists and Wikimedians can go further by looking at probability of having a biography though Wikipedia edition, country, year of birth and gender.

In the future, the dataset could be extended to a larger number of Wikipedia editions and to other Wikimedia projects such as Wikiquote, Wikisource and Wikidata.

Further research would be valuable to understand what drives these disparities. In particular, it would be worth investigating whether the gap stems from differing likelihoods of meeting the notability criteria, or from how those criteria are interpreted across Wikipedia communities.

This article was originally published by Wikimedia Foundation on October 5, 2026 on Diff and licensed CC-BY-SA 4.0. A discussion about this article is taking place at the WMF section of the village pump.

Recently, multiple organisations have disclosed how clusters of so-called “rogue” AI agents attempted to break into websites and online services, sometimes successfully. Agents from OpenAI’s environment, in particular, are known to have used other public wikis (collaboratively edited websites not owned by us) to communicate and coordinate with each other.

These types of successful intrusions can expose sensitive data or disrupt website services that users rely on, while clusters of agents can attempt attacks at a scale that is difficult for defenders to manage. They affect people behind the websites who may not understand the nature of the attack or have the tools to effectively fight back. For a site like Wikipedia, agents might find and use security vulnerabilities or make misleading edits at scale. Wikipedia’s volunteer editors and the Wikimedia Foundation’s security teams have to detect and undo that activity.

The Wikimedia Foundation conducted its own investigation to see whether Wikimedia websites had been similarly affected by AI agents, focusing on those operated by OpenAI. We can confirm that we have discovered some activity by these “rogue” OpenAI agents on Wikimedia platforms. The unauthorized bot activities included edits to our wikis, some unsuccessful attempts to exploit a public note-taking tool we host, and heavy traffic, which are described more below.

We did not find any evidence that our systems were used for coordination among agents, nor did we find any evidence of our systems or data being compromised. However, we are concerned about what could have occurred here, the difficulty and effort involved in investigating and attributing this activity, and the growing risks of agentic AI activity on our platforms in general. The open web is a public good. We should not allow this behavior to become the "new normal" for the people or organizations that maintain it.

In summary, we saw:

• Wiki editing: We’ve identified edits to Wikimedia wikis that we believe are from AI agents operated by OpenAI. These edits were not published to pages with visibility to general readers; almost all of them were testing edits in “sandbox” areas of the wiki. It also included a few edits to the configuration for a citation tool, which we believe were potentially malicious edits that were intended to misuse this tool as a proxy for fetching data from remote services. While Wikipedia policies allow bots to edit when they are disclosed and approved by the community, none of those approvals were sought in these incidents.
• Etherpad probing and use: Agents we believe to be operated by OpenAI made some unsuccessful attempts to compromise our public Etherpad, a note-taking tool we host as a community service. Agents unsuccessfully tried to use it to fetch data from other websites as a proxy. Other agents also likely operated by OpenAI took notes about their tasks, though this did not appear to turn into coordination.
• Excessive data downloading: Agents we believe to be operated by OpenAI made millions of automated requests to our public APIs to access the knowledge on Wikimedia projects, crawled millions of pages (mainly from our projects Wikidata and Wikimedia Commons), and made hundreds of thousands of data queries to the Wikidata Query Service (WQDS). This traffic may have contributed to a partial outage on WQDS in May.

As a non-profit technology host of some of the largest and most widely used open knowledge platforms in the world, we are deeply concerned about the impact of “rogue” AI agents on platforms like ours, which are built by volunteers from around the world and rely on the promise of the open internet. Incidents like this one, and the many others that have been (and are still being) uncovered, illustrate how AI agents can drain resources and crash servers, as well as attempt to compromise trustworthy information.

Over the past 25 years, Wikipedia has grown into one of the most popular and trusted websites in the world, with more than 67 million articles across over 300 languages, and up to 15 billion page views per month. Through an open, transparent, and collaborative process, volunteers work to ensure that knowledge remains neutral, reliable, and accessible to everyone. Wikipedia is one of the highest-quality datasets used in training Large Language Models (LLMs), and its knowledge forms the backbone of information on the internet, powering AI chatbots, search engines, voice assistants, and more.

Wikipedia was designed for humans – and agentic behavior clearly poses challenges that no one has solutions for. Because of our unique and successful knowledge creation model, Wikimedia’s volunteers are the ones who come in first contact with, and clean up the mess left behind by AI agents. Rising bot traffic and agentic activity are showing a real impact on the Wikimedia projects and the infrastructure that makes it available for millions of users globally. In 2025, the Foundation reported that its bandwidth usage had increased by 50% due to the surge of bot activity on its websites since 2024. At the same time, 65% of the most resource-consuming traffic on its projects was coming from bots.

This intense pressure on our infrastructure not only adds costs for servers and humans, but if left unaddressed, can block human visitors by overloading systems and causing outages. We are already paying for costs that come with the increased activity.

Wikimedia’s volunteers have stayed resilient so far in tackling emerging challenges on our platforms, but we also want to say: it doesn’t need to be this way.

While OpenAI admits to agents behaving “unpredictably”, they must also acknowledge their responsibility to monitor and prevent these risks. AI companies are not doing enough to secure their systems and protect the public from the harm they cause. That burden is falling onto everyone else, including smaller organizations. At a minimum, their systems should operate in a way that non-profit website owners like us can easily identify and choose how they interact with our services.

The web enables so much: to connect with friends and family, to register for school, to plan a trip across town, to buy groceries, and to learn about the world from Wikipedia. Bots and agents are part of the future of the web, and the companies that unleash and profit from them must directly help avoid and repair the damage they can do.

Our collective priority should be the health of the overall web ecosystem so that it continues to benefit all people – not just a handful of billionaires. Wikimedia plays a critical role in stewarding the knowledge commons, but we cannot do it alone. We invite everyone who is building the future of the web to join us in protecting the open, shared resources that make that future possible.

Here is a refreshing suggestion from one of our colleagues:

Our work together here should be our armor, not some sharp, angry, burning sword. I would strongly recommend that everyone here find an article to work on for a while; not the cliche "random article", but something that gives you a nice tug at the heartstrings. It feels great to be out there doing work on something you genuinely care about, and I assure you it'll help you regain the sense of why you're here.
— User:The Blade of the Northern Lights

On 30 September 2026, Wikipedians were informed by the daughter of User:Doug Weller of Doug's passing. An obituary piece is included in this issue of The Signpost. Many kind comments have been left on Doug's talk page. Below is a selection of those that included multimedia.

	The Admin's Barnstar
	My condolences, and please rest in peace. 16dvnk (talk) 11:24, 4 October 2026 (UTC)reply

	The Special Barnstar
	Thanks for your contributions, Doug. St☆rlet! (Need to talk?) (Library) (Sandbox) 22:02, 4 October 2026 (UTC)reply

	The Original Barnstar
	For the amazing being you were, Doug. For all the guidance and love you have shown me, and the community. Rest is peace, king. You'll be missed. — Benison (Beni · talk) 03:08, 6 October 2026 (UTC)reply

Ad astra, Doug. May this creature keep you comfort in whatever you think comes next.

LakesideMiners^{Come Talk To Me!} 17:18, 8 October 2026 (UTC)reply

	The Admin's Barnstar
	We'll take over now. You have our word. We miss you already, too. Tankishguy 13:47, 9 October 2026 (UTC)reply

"Chì mi na mòrbheanna"

A recording of the Scottish Gaelic song by Iain Camshron, performed by the United States Air Force Reserve Pipe Band

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Problems playing this file? See media help.

Rest well, Doug. Thank you for the decades of service here. This community honors you. ༄ᨒ𖠰 Pine (✉) 04:21, 13 October 2026 (UTC)reply

This week I was grateful to learn off-wiki that Seattle Mountain Rescue received a second mobile command vehicle.

Also, I learned from that, after a vehicle incident, an army practical nursing instructor who is stationed at a base near me intervened with others to save two children. While the whole story is sadder than I feel belongs in On The Bright Side, I am grateful for the initiative and courage of the soldier and others who assisted.

I am reminded of this quote:

I encourage everyone to learn first aid, mental health first aid, and for those who like to go hiking, the "Ten Essentials".

This gallery is a selection of photos of professional coast guard, professional and volunteer search and rescue, and volunteer firefighter activities and equipment from several countries.

• Coast guard, search and rescue, and firefighting
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Skillful translations of the sentence "What's making you happy this week?" would be very much appreciated. If you see any inaccuracies in the translations in this article, then please {{ping}} User:Pine or User:Clovermoss in the discussion section of this page, or boldly make the correction to the text of the article. Thank you to everyone who has helped with translations so far.

What makes you happy or grateful this month? You are welcome to write a comment on the talk page of this Signpost piece.

This traffic report is adapted from the Top 25 Report, prepared with commentary by Igordebraga, Hason-LEK-SIN (September 6 to October 3), Rahcmander (September 6 to 12), Bkissin (September 13 to October 3) and VidanaliK (September 27 to October 3).

Rank	Article	Class	Views	Image	Notes/about
1	Christa Pike		9,000,316		A convicted murderer and the subject of a botched execution in Tennessee on September 30. Unlike most of the other 21 U.S. states which administer lethal injections using a three-drug protocol (one to make the subject unconscious, one to paralyze them, and one to stop the heart), Tennessee simply uses one drug, pentobarbital, to kill the subject, and has no backup protocol after four doses of pentobarbital are administered. After the injection, Pike was left unconscious in a hospital with severe burns.
2	2026 Asian Games medal table		2,855,058		As with most sporting events, people on the internet (well, except China, which have their own internet) want to check how their team's doing at the Asian Games (#5). The top three remain China, Japan, and South Korea, with 341, 269, and 150 medals respectively, according to this version. Interestingly, Bahrain is 10th while Malaysia is just trailing behind at 11th, which sounds too close to be a coincidence given that the 2026 Bahrain Grand Prix is taking place in Malaysia just as this Report is being written.
3	India at the 2026 Asian Games		2,268,487		Given India has the world's largest population (or second to China depending on which dataset you're looking at), it's fitting that it also has the third largest Wikipedia readership (493 million in September per Wikimedia Stats. India did pretty well at the 2026 Asian Games, earning 21 gold medals, 27 silver medals, and 37 bronze medals. Some of its most successful sports included archery, boxing, cricket, squash, wrestling, and shooting, where it earned 15 medals. Four Indian athletes, Sahil Jadhav (the only athlete we have a picture for), Kumkum Mohod, Neeru Dhanda, and Chikitha Taniparthi, won two gold medals, but 28 athletes were multiple medalists in general. India also had several notable firsts, including the first Indian woman to win gold in the shotgun event (Neeru Dhanda), and to win individual recurve gold (Kumkum Mohod). The delegation also had a roughly equal split between men and women.
4	Lizzie Borden		1,817,901		The subject of the fourth season of Monster already was the first female, and the first that wasn't proven to have killed someone. Here on Wikipedia, it also became the first to not break 5 million views in a week or lead our Report for three weeks straight (ironically being overtaken at the top spot by an actual murderer).
5	2026 Asian Games		1,817,056		The second appearance of the Games, after which next week will likely be the last appearance as the Games close on 4 October. Good news for the writer: Loh Kean Yew has beaten Jonatan Christie, securing Singapore's first badminton silver at the Asian Games, joining Shanti Pereira and Gan Ching Hwee as one of Singapore's medalists. Bad news: Singapore dropped from #19, when we checked last week, to #21. Even worse news: a typhoon had hit Tokyo (some sports were hosted there) before the games. Worst of all: there's way too many controversies (the mayor had to apologise). Given how the 2026 Winter Olympics (albeit minor) and the 2026 FIFA World Cup have their own share of controversies, does the world really want the writer to believe that the 2026 NBA Finals was the best sporting event of 2026? Maybe even ever? Then again this comparison does sound relatively apples to oranges, but still.
6	Ted Kaczynski		1,740,143		While #4 was never proven to have killed her parents, the Unabomber indeed caused 3 deaths and 23 injuries with his homemade explosives. And less than a week after Borden's miniseries, Netflix added a movie about Kaczynski, Unabomber, where the professor-turned-hermit-turned-terrorist is played by Jacob Tremblay.
7	Pac (wrestler)		1,281,311		Real name Benjamin Satterley, and not to be confused with X-Pac or Pac-Man, this former English professional wrestler died at age 40 in Illinois on 27 September, just a day after All Out (2026) took place, after a member of the public found him unresponsive in a rental car. Tributes to him came from across the professional wrestling community, and an event to him, A Tribute to Pac, took place, alongside a special episode of AEW Dynamite.
8	Case Keenum		1,094,210		In the first of two longtime American athletes on the Top 25, the third-string Quarterback for the Chicago Bears led an impressive win over the Philadelphia Eagles on Monday Night Football. Keenum, a longtime Journeyman quarterback who went undrafted in 2012, was previously known for leading the 2017 Minnesota Vikings to the NFC Championship, where they were beaten by the Eagles and Keenum was fired. Keenum's children had never seen him play prior to Monday night's game, where Keenum's daughter joined him for the post-game interview.
9	Deaths in 2026		1,003,293		If I could save time in a bottle The first thing that I'd like to do Is to save every day 'Til eternity passes away...
10	2024 Cornell University rape allegations		958,450[1]		An unnamed former student of Cornell University sued the university and its Chi Phi chapter claiming that in 2024, she was gang raped by seven members of that fraternity (nicknamed "Cornell 7", though the name has been criticized for similarities to the "Central Park Five" that turned out to be innocent). Cornell has suspended the seven, two of whom were expelled, and the university also closed Chi Phi. As investigation rolls, two of the accused denied taking part in the assault, while a third said that at least regarding him, the sex was consensual.

• These lists exclude the Wikipedia main page, non-article pages (such as redlinks), and anomalous entries (such as DDoS attacks or likely automated views). Since mobile view data became available to the Report in October 2014, we exclude articles that have almost no mobile views (5–6% or less) or almost all mobile views (94–95% or more) because they are very likely to be automated views based on our experience and research of the issue. Please feel free to discuss any removal on the Top 25 Report talk page if you wish.