Wikipedia bias explained смотреть последние обновления за сегодня на .
I love Wikipedia! I even donated to it. But I won't donate again, now that I've learned how BIASED Wikipedia has become. ———— To make sure you see the new weekly video from Stossel TV, sign up here: 🤍 ———— No right-leaning outlets, Fox News Politics, the Daily Wire, the Daily Caller, etc… is considered “reliable” by Wikipedia. None. But even some of the most extreme leftist outlets get a "reliable" badge like “Jacobin," a self-described SOCIALIST outlet. Vox, Buzzfeed News, and Slate are also deemed “reliable” by Wikipedia. Editors may base stories on their reporting. Why did Wikipedia become so biased? Veteran Wikipedian Jonathan Weiss tells me that the site, like academia, has been captured by leftists. Some Wikipedia administrators even brag on their profiles, "this user is a socialist." Another put up images idolizing communist murderers Che Guevara and Vladimir Lenin. These administrators make final decisions about what counts as “reliable," and what goes on Wikipedia. That’s why for years, Wiki's "communism" page made NO mention of the millions killed by that ideology. US border facilities are listed under "concentration camps,” on the same page as Wikipedia’s holocaust facilities. Can we fix this? Wikipedia is supposed to be a site that "anyone can edit," so I made an edit. You can find out what happened in the video above.
Wikipedia is the #1 research tool in the world, boasting over 18 billion views per month. It also pushes a radical left-wing agenda. Crowder and crew expose how they do it. #Wikipedia #Bias #FactCheck Go to 🤍 and use promo code “Crowder15” to get 15% off your next order. Try the Walther! Visit 🤍 to shop online or use the dealer locator to find a Walther dealer near you! NEW MERCH! 🤍 GET TODAY'S SHOW NOTES with SOURCES: 🤍 Join MugClub to watch this show every day! 🤍 Subscribe to my podcast on iTunes: 🤍 FOLLOW ME: Website: 🤍 Twitter: 🤍 Instagram: 🤍 TikTok: 🤍 Snapchat: 🤍 Facebook: 🤍 Shoutout: 🤍 Music by 🤍Pogo
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Lex Fridman Podcast full episode: 🤍 Please support this podcast by checking out our sponsors: - Hexclad Cookware: 🤍 and use code LEX to get 10% off - Eight Sleep: 🤍 to get special savings - House of Macadamias: 🤍 and use code LEX to get 20% off your first order GUEST BIO: Jimmy Wales is the co-founder of Wikipedia. PODCAST INFO: Podcast website: 🤍 Apple Podcasts: 🤍 Spotify: 🤍 RSS: 🤍 Full episodes playlist: 🤍 Clips playlist: 🤍 SOCIAL: - Twitter: 🤍 - LinkedIn: 🤍 - Facebook: 🤍 - Instagram: 🤍 - Medium: 🤍 - Reddit: 🤍 - Support on Patreon: 🤍
Help Support Weight Loss With This Secret Powder I Use ➡️ 🤍 ⬅️ Get FREE express delivery! Click Here ^^^^ ———————————————————————— ★★★ THE POPULIST REVOLT HAS JUST BEGUN ★★★ The co-founder of Wikipedia is SLAMMING the site for its Left-wing Bias, and this co-founder is doing something about it: He’s LAUNCHING His Own Alternative Free-Speech Site! In this video, we’re going to take a look at the ridiculously leftist bias that pervades Wikipedia, how the co-founder is actively launching a free-speech alternative, and how his launch is part of a larger world of parallel structures that promise a future free from the ridiculous cancel culture tyranny of the modern left! You are NOT going to want to miss this! ———————————————————————— ►FIGHT BACK AGAINST BIG TECH CENSORSHIP! SUBSCRIBE to my Brand-New RUMBLE Channel here: 🤍 ———————————————————————— ►PARLER IS BACK! Click Here to Subscribe to our NEW Parler feed: 🤍 ———————————————————————— ✅ LIMITED TIME OFFER! Get Your Copy of My Book RETURN OF CHRISTENDOM at a 50% DISCOUNT Here ➡️🤍 ———————————————————————— ►Help us REACH #1 with our NEW PODCAST PROGRAM! Download your podcasts here 🤍 ———————————————————————— ►Brought to you by Liberty Water: Working to quench the thirst of freedom-loving Americans. Get your water today at 🤍 ———————————————————————— ❤ WELCOME, EVERYONE!!! ❤ It's WONDERFUL to have you HERE! I post two videos a day analyzing current events in light of conservative trends so you can live in the present in light of even better things to come! ⚑ SHARE AND SUBSCRIBE TO MY CHANNEL ⚑ 🤍 ———————————————————————— ►BECOME A TURLEY TALKS INSIDERS CLUB MEMBER: 🤍 ►FIGHT BACK AGAINST BIG TECH CENSORSHIP! Sign-up here to discover Dr. Steve’s different social media options …. but without the censorship! 🤍 ►Download your own ‘Fake News Antidote’ Ebook here: 🤍 ✉ LET'S KEEP IN TOUCH! ✉ Make sure to sign-up for our ✉ TURLEY TALKS Email NEWSLETTER ✉ here: 🤍 ►FIGHT BACK AGAINST BIG TECH CENSORSHIP! Subscribe to my GAB PLATFORM: 🤍 ►Subscribe to my Brand-New RUMBLE Channel here: 🤍 ►Find me on BITCHUTE: 🤍
Let's talk about Wikipedia. Wikipedia is often maligned by teachers and twitter trolls alike as an unreliable source. And yes, it does sometimes have major errors and omissions, but Wikipedia is also the Internet's largest general reference work and as such an incredibly powerful tool. Today we'll discuss using Wikipedia for good - to help us get a birds-eye view of content, better evaluate information with lateral reading, and find trustworthy primary sources. Special thanks to our partners from MediaWise who helped create this series: The Poynter Institute The Stanford History Education Group (sheg.stanford.edu) Follow MediaWise and their fact-checking work across social: 🤍 🤍 🤍 🤍 MediaWise is supported by Google. Crash Course is on Patreon! You can support us directly by signing up at 🤍 Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Eric Prestemon, Sam Buck, Mark Brouwer, Naman Goel, Patrick Wiener II, Nathan Catchings, Efrain R. Pedroza, Brandon Westmoreland, dorsey, Indika Siriwardena, James Hughes, Kenneth F Penttinen, Trevin Beattie, Satya Ridhima Parvathaneni, Erika & Alexa Saur, Glenn Elliott, Justin Zingsheim, Jessica Wode, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Brian Thomas Gossett, Khaled El Shalakany, SR Foxley, Yasenia Cruz, Eric Koslow, Caleb Weeks, Tim Curwick, D.A. Noe, Shawn Arnold, Malcolm Callis, Advait Shinde, William McGraw, Andrei Krishkevich, Rachel Bright, Jirat, Ian Dundore Want to find Crash Course elsewhere on the internet? Facebook - 🤍 Twitter - 🤍 Tumblr - 🤍 Support Crash Course on Patreon: 🤍 CC Kids: 🤍
Vanessa Otero set out to rank an ever-growing partisan media landscape, with the belief that an informed public is a better public. Learn more about this story at 🤍 Find more videos like this at 🤍 Follow Newsy on Facebook: 🤍 Follow Newsy on Twitter: 🤍
It's the go-to website for information on just about anything. But is the info on Wikipedia worth it's weight in megabytes? Trace has the answer and tells us about a new plan to up the accuracy of some of its most popular pages. Read More: UCSF First U.S. Medical School to Offer Credit For Wikipedia Articles 🤍 "UC San Francisco soon will be the first U.S. medical school at which medical students can earn academic credit for editing medical content on Wikipedia." Medical Students Can Now Earn Credit for Editing Wikipedia 🤍 "Starting this winter, medical students at the University of California San Francisco will be able to obtain academic credit from an unlikely source: Wikipedia." Using Wikipedia 🤍 "As a tool for scholarly research, Wikipedia can be either a grade-killer or a valuable friend, depending on who you ask and what you hope to accomplish using it. What is fairly certain is that your professor won't let you cite it in a scholarly research paper." Citing Wikipedia 🤍 Most university lecturers discourage students from citing any encyclopedia in academic work, preferring primary sources; some specifically prohibit Wikipedia citations. Wales stresses that encyclopedias of any type are not usually appropriate to use as citeable sources, and should not be relied upon as authoritative." Special Report Internet encyclopaedias go head to head 🤍 "Jimmy Wales' Wikipedia comes close to Britannica in terms of the accuracy of its science entries, a Nature investigation finds." Britannica attacks... and we respond. 🤍 Watch More: Are We All Internet Addicts? 🤍 Scientists Vs Internet Trolls 🤍 7 NEW Wonders Of the World: 🤍 DNews is dedicated to satisfying your curiosity and to bringing you mind-bending stories & perspectives you won't find anywhere else! New videos twice daily. Watch More DNews on TestTube 🤍 Subscribe now! 🤍 DNews on Twitter 🤍 Anthony Carboni on Twitter 🤍 Laci Green on Twitter 🤍 Trace Dominguez on Twitter 🤍 DNews on Facebook 🤍 DNews on Google+ 🤍 Discovery News 🤍
Presentation from the Research track during Wiki Workshop 2023. See here for more information on authors and their papers: 🤍
At our July WMAU Community Meeting Gianluca Demartini, Associate Professor in Data Science at the University of Queensland, spoke about his research around Wikidata and Wikipedia. Read more about Gianluca’s work at his University of Queensland Research Profile: 🤍 In the video, Gianluca mentions the following article and paper: The evolution of power and standard wikidata editors: comparing editing behavior over time to predict lifespan and volume of edits (2019). You can read it here: 🤍 Non-parametric class completeness estimators for collaborative knowledge graphs—the case of Wikidata (2019). You can read it here: 🤍 For future community meetings and events see our website: Wikimedia Australia: 🤍
This is an audio version of the Wikipedia Article: 🤍 00:03:01 1 Definition and context 00:04:23 1.1 Biased search for information 00:12:05 1.2 Biased interpretation 00:18:27 1.3 Biased memory 00:24:07 2 Individual differences 00:27:39 3 Historical Observations 00:31:38 4 Initial hypothesis-testing studies 00:37:08 5 Information processing explanations 00:37:31 5.1 Cognitive versus motivational explanations 00:40:36 5.2 Cost-benefit explanation 00:43:04 5.3 Exploratory versus confirmatory explanations 00:44:42 5.4 Make-believe explanation 00:45:31 6 Real-world effects 00:45:41 6.1 Social media 00:46:49 6.2 Finance 00:47:48 6.3 Physical and mental health 00:49:26 6.4 Politics and law 00:51:52 6.5 Science 00:54:56 6.6 Social psychology (the self) 00:56:04 6.7 Paranormal beliefs 00:57:43 7 Related effects 00:57:53 7.1 Polarization of opinion 01:03:34 7.2 Persistence of discredited beliefs 01:06:33 7.3 Preference for early information 01:08:54 7.4 Illusory association between events 01:11:32 8 See also Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: 🤍 Other Wikipedia audio articles at: 🤍 Upload your own Wikipedia articles through: 🤍 Speaking Rate: 0.7448454187085253 Voice name: en-GB-Wavenet-D "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY = Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms one's preexisting beliefs or hypotheses. It is a type of cognitive bias and a systematic error of inductive reasoning. People display this bias when they gather or remember information selectively, or when they interpret it in a biased way. The effect is stronger for desired outcomes, emotionally charged issues, and for deeply entrenched beliefs. Confirmation bias is of particular current interest because of the increasing polarisation between left-wing and right-wing political viewpoints, and the gullible acceptance of the current rapid spread of fake news.People also tend to interpret ambiguous evidence as supporting their existing position. Biased search, interpretation and memory have been invoked to explain attitude polarization (when a disagreement becomes more extreme even though the different parties are exposed to the same evidence), belief perseverance (when beliefs persist after the evidence for them is shown to be false), the irrational primacy effect (a greater reliance on information encountered early in a series) and illusory correlation (when people falsely perceive an association between two events or situations). A series of psychological experiments in the 1960s suggested that people are biased toward confirming their existing beliefs. Later work re-interpreted these results as a tendency to test ideas in a one-sided way, focusing on one possibility and ignoring alternatives. In certain situations, this tendency can bias people's conclusions. Explanations for the observed biases include wishful thinking and the limited human capacity to process information. Another explanation is that people show confirmation bias because they are weighing up the costs of being wrong, rather than investigating in a neutral, scientific way. However, even scientists and intelligent people can be prone to confirmation bias.Confirmation biases contribute to overconfidence in personal beliefs and can maintain or strengthen beliefs in the face of contrary evidence. Poor decisions due to these biases have been found in political and organizational contexts.
Daren Welsh 🤍 Humans are prone to bias and noise. Algorithms can mitigate noise from humans, but bias can be programmed into algorithms by human developers. If we use wikis to help us make critical decisions, how do we identify and mitigate bias in our algorithms? EMWCon, or the Enterprise MediaWiki Conference, is an annual event, first held in 2016, which includes talks, workshops and tutorials relating to the use of MediaWiki outside of Wikimedia sites, including by companies, organizations and government agencies. It was spun off from SMWCon, or the Semantic MediaWiki Conference, which began as a twice-annual event in 2010 but became once-annual in 2016. EMWCon is generally held in the United States in the spring, while SMWCon is generally held in Europe in the fall. Produced by NDV: 🤍 Wed Apr 3 14:45:00 2019 at Genesys
Wikipedia is biased. Water is wet. Nothing new under the sun. Still, I want to present a particularly egregious example. Naomi Seibt is a talented Youtuber who graduate from College (actually the German equivalent 'Gymnasium') at only sixteen years of age. Whilst still in school she competed successfully in widely respected math and physics competitions, winning second and first place respectively. #Wikipedia, though, paints her differently, very differently, you know...Nazi. But, of course, this is not the used word. The innuendo game is well-known already. Random voices are quoted that accuse her of 'white nationalism' and 'antisemitism.' Outright lies are included. Her poem 'Sometimes I Keep Silent' were about 'nationalism' when the title already says what it is actually about: the silence. (The #poem can be found here: 🤍 Use an automated translation tool of your choice if you wish.) She was even inspired by Stefan Molyneux. - You mean the Canadian Youtuber? Thank you for asking. I'm not sure because on Naomi Seibt's Wikipedia entries, both the English and the German one, he is also a Nazi. She also "dismisses" the allegations that she were a "puppet" of the right wing. How dare you! The #Heartland Institute, where she worked, is described as pseudo-scientific. And the culprit behind our lack of scientific knowledge is also found: the old white man. The Silicon Valley bias, like the media bias, is much more intense against people who dare to talk about politics outside of the English-speaking world. Consequently, it is no surprise that even Richard Grenell, former US Ambassador to Germany, is accused of mingling with the "far right" (Grenell is homosexual.)
For more information, please, visit: 🤍 This is an audio version of a Wikipedia article created for the benefit of those who have vision problems or problem reading at night. This Wikipedia article audio was created under Creative Commons Attribution-ShareAlike. To view the original article, go to 🤍
Access the prototype here 🤍 + info 🤍 The aim of this research project is to improve the exploration experience of underpriviledged communities in creative archives. At the moment we have created a web app that will help individuals to explore a topic of their choice in Wikipedia and provide information (a feedback) that will highlight the type of stereotypical biases (memory transgressions towards stereotypes such as gender, race, economic background etc.) that characterize each information.
Wikipedia biases Over the last year, scientist Jess Wade has taken to the keyboard to rectify gender bias on Wikipedia. She has written more than 270 entries about forgotten but influential women in science – such as Susan Goldberg, the first female editor of National Geographic. Research shows just 16% of Wikipedia editors are female and only 17% of entries dedicated to notable people are for women. Facebook Twitter Pinterest Young Nigerian woman at a social media conference in Lagos. Most coverage of sub-Sahar...
#Attentionalbias #audioversity ~~~ Attentional bias ~~~ Title: What is Attentional bias?, Explain Attentional bias, Define Attentional bias Created on: 2018-12-09 Source Link: 🤍 Description: Attentional bias is the tendency for people's perception to be affected by their recurring thoughts at the time. Attentional biases may explain an individual's failure to consider alternative possibilities, as specific thoughts guide the train of thought in a certain manner. For example, smokers tend to possess a bias for cigarettes and other smoking-related cues around them, due to the positive thoughts they've already attributed between smoking and the cues they were exposed to while smoking. Attentional bias has also been associated with clinically relevant symptoms such as anxiety and depression. To see your favorite topic here, fill out this request form: 🤍 Source: Wikipedia.org articles, adapted under 🤍 license. Support: Donations can be made from 🤍 to support Wikimedia Foundation and knowledge sharing.
This is an audio version of the Wikipedia Article: 🤍 00:01:01 1 Etymology 00:01:47 2 Types of bias 00:01:57 2.1 Cognitive biases 00:03:17 2.1.1 Anchoring 00:04:02 2.1.2 Apophenia 00:04:55 2.1.3 Attribution bias 00:06:04 2.1.4 Confirmation bias 00:07:31 2.1.5 Framing 00:09:23 2.1.6 Halo effect and horn effect 00:10:54 2.1.7 Self-serving bias 00:11:43 2.1.8 Status quo bias 00:12:33 2.2 Conflicts of interest 00:13:30 2.2.1 Bribery 00:14:34 2.2.2 Favoritism 00:15:24 2.2.3 Lobbying 00:16:27 2.2.4 Regulatory issues 00:18:05 2.2.5 Shilling 00:18:46 2.3 Statistical biases 00:19:26 2.3.1 Forecast bias 00:19:48 2.3.2 Observer-expectancy effect 00:20:18 2.3.3 Reporting bias & social desirability bias 00:21:39 2.3.4 Selection bias 00:22:16 2.4 Prejudices 00:23:10 2.4.1 Classism 00:23:31 2.4.2 Lookism 00:24:00 2.4.3 Racism 00:24:23 2.4.4 Sexism 00:24:54 3 Contextual biases 00:25:04 3.1 Biases in academia 00:25:14 3.1.1 Academic bias 00:26:10 3.1.2 Experimenter bias 00:26:46 3.1.3 Funding bias 00:27:26 3.1.4 Full text on net bias 00:28:25 3.1.5 Publication bias 00:29:27 3.2 Biases in law enforcement 00:29:37 3.2.1 Driving while black 00:30:02 3.2.2 Racial profiling 00:30:35 3.2.3 Victim blaming 00:30:58 3.3 Biases in media 00:32:29 3.3.1 Agenda setting 00:32:54 3.3.2 Gatekeeping 00:33:37 3.3.3 Sensationalism 00:34:13 3.4 Other contexts 00:34:22 3.4.1 Educational bias 00:35:26 3.4.2 Inductive bias 00:36:33 3.4.3 Insider trading 00:37:15 3.4.4 Match fixing 00:38:15 4 See also Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: 🤍 Other Wikipedia audio articles at: 🤍 Upload your own Wikipedia articles through: 🤍 Speaking Rate: 0.8857685412406577 Voice name: en-US-Wavenet-B "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY = Bias is disproportionate weight in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair. Biases can be learned implicitly within cultural contexts. People may develop biases toward or against an individual, an ethnic group, a sexual or gender identity, a nation, a religion, a social class, a political party, theoretical paradigms and ideologies within academic domains, or a species. Biased means one-sided, lacking a neutral viewpoint, or not having an open mind. Bias can come in many forms and is related to prejudice and intuition.In science and engineering, a bias is a systematic error. Statistical bias results from an unfair sampling of a population, or from an estimation process that does not give accurate results on average.
Exploring Systematic Bias through Article Deletions on Wikipedia from a Behavioral Perspective Zena Worku, Taryn Bipat, David W. McDonald & Mark Zachry University of Washington, Human Centered Design and Engineering Full paper Opensym 2020 presentation will be on August 15th at 15:00 UTC The gender gap in participation on Wikipedia is well established. The impacts of the participation bias on content may be expressed through a number of different behaviors. This research considers potential content biases that may result from efforts to delete content. We collect deletion data on a sample of article pages selected based on a method designed to identify content of likely interest to a specific group of people; men and women in this case. The analysis illustrates that there does not appear to be a systematic bias resulting in more deletions or nominations for deletions against content of likely interest to women. We consider how these results improve our understanding of bias and the ways peer production systems can mitigate the potential for biases.
Wikipedia Weekly podcast, index: 00:00:00 Introductions 00:01:01 WikiPR update 00:15:15 WikiVIP and multimedia in Wikipedia 00:21:36 RfC on video support across Wikimedia projects 00:38:11 Andrew's American University Wikipedia class 00:46:48 Which news sources Wikipedia uses the most 00:53:04 Plotting Wikipedia's geodata on maps 00:54:51 State of Wikipedia:Requests for adminship 01:22:22 popular articles of the last week
For years, Wikipedia - the world's largest online encyclopaedia - has ranked among the top visited websites in the world. It is likely the first result to pop up on an internet search. And since 2001, the "Free Encyclopaedia" has become a key source for online discovery and research. But more than 80% of Wikipedia's volunteer editors are male, and the gender imbalance is reflected in its articles, say Wikipedians working to address the site's gender bias and lack of inclusivity. Over the years, numerous efforts by the Wikimedia Foundation and others have been made to encourage more articles and citations focused on highlighting the accomplishments of women. Wikipedia entries about women are less likely to be accepted and annotated by its online community of editors. A 2021 study found that 41% of Wikipedia biographies nominated for deletion were about women. That figure seems staggering given that only 19% of published Wikipedia biographies are about women, according to the Wikiproject Women in Red. In this episode of The Stream, we’ll look at some of the editing initiatives that are working to fight gender bias, one Wikipedia entry at a time. Join the conversation: TWITTER: 🤍 FACEBOOK: 🤍 Subscribe to our channel 🤍 #aljazeeraenglish #ajstream #wikipedia
Used NLP techniques to detect differences in the language used by different media sources to determine the biases inherent in the language. He classified articles from various sources from a selection of news sources across the political spectrum from far let to far right into categories based on their bias.
Source: 🤍 Wikipedia's Culture of Institutional Bias Richard Gale and Gary Null Progressive Radio Network, June 11, 2019 Weekly, millions of people Google their concerns about their health and a large variety of illnesses, such as heart disease, cancer, diabetes, dementia, etc. They expect, with speed and accuracy, to find the current scientifically based and clinically proven information. The majority of people begin to approach a personal health crisis by turning exclusively to established medical, drug-based protocols. However, these treatments do not always relieve symptoms nor reverse disease. Certainly they do not prevent it. Increasingly people are seeking second and third opinions. More often than not Google will take a person immediately to Wikipedia. There is an assumption and a reasonable expectation that the information we find on Wikipedia is 1) accurate, 2) soundly researched and referenced from high quality and reliable resources, 3) written by credentialed writers and editors with expertise in the subject, 4) unbiased, and finally 5) object and balanced. Therefore it is at minimal assumed that at least the content on Wikipedia is scientifically validated and would appear on the National Institutes of Health PubMed database for medical information and research. Whether it is pharmaceutical, surgical or radiological approach, or perhaps a more natural medical modality such as lifestyle change, nutrition, medical botanicals, Chiropractic and Chinese Medicine, it is expected the information will be accurately provided and described. Then using our freedom of choice and informed consent, we can select the medical route that we believe would be most safe and effective. Unfortunately, our two year investigation into Wikipedia's treatment of health issues reveals exactly the opposite. In fact, there are many individuals with outstanding credentials who are terrified of having their biographies appear on the open-source encyclopedia. Once a person's biography is added they will never have control over its content. Often he or she will be faced with slander, character assassination and denigration about their careers and life's work. All efforts by attorneys and experts in their field will not be able to change a single syllable on a Wikipedia page. Their biographies are frozen as if confined in a Russian gulag for a political crime. They will seek redress by reaching out to the media; but the media too is fully compromised. They may seek open hearings on Wikipedia's back side to expose unfair behavior and misinformation but will be met either by deafening silence or censorship. They may even seek redress from the IRS or state's attorney generals for Wikipedia's gross serial violations of its non-profit status. Consequently, it becomes political and assumingly nothing will happen to correct the errors. As a result, a relatively small group of uncredentialed, hate-filled individuals commonly known as Skeptics, empowered by Wikipedia's co-founder Jimmy Wales, have been using the encyclopedia as a social media platform to condemn all non-conventional and alternative medical therapies and its practitioners, even those who seek to benefit from these therapies. There are hundreds of thousands of clinical trials, research papers and review analyses confirming the authenticity and effectiveness of these natural medical systems. However, for the Skeptics who control and edit these Wikipedia pages, knowing full well that they have Jimmy Wales’ unerring support, the truth is irrelevant. Today Wikipedia succeeds the worst of McCarthyism's witch hunts in the 1950s where there is no proper channel for redress. Even attorneys representing the Silicon Valley titans, Wikipedia among them, have gamed the system. Should we ask the media 20-20, Nightline, 60 Minutes, the New York Times and all the other leading newspapers and magazines why they fail to protect the American and global public from misinformation on a social platform and indulge in a shameful complicity to permit Wikipedia’s deception to continue without proper review and public exposure? Yet none have the guts to undertake an objective investigation to uncover the truth. Below is a detailed review about what we have uncovered. For deeper investigations about how Wikipedia is on all accounts an enemy of public health, we invite readers to read more thorough articles at 🤍 Wikipedia and the Medical Profession In 2012, Americans spent $14.7 billion on Complementary and Alternative Medicine (CAM) and non-conventional medical services, such as chiropractors, massage therapies, acupuncturists, and energy medical practitioners and healers. This is almost a third of what is personally spent on conventional medical services. In addition, $12.8 billion was spent on natural supplements, accounting for approximately 25% of what Americans spend
In this video I cover some recent and major revisions that have recently been made to vs battle wiki and I uncover what I believe to be a both hypocritical and severe bias against the Naruto verse within VSB. My Discord- 🤍 My Twitter- 🤍 Surfbone's channel- 🤍 Link to KingBullet's Universal Naruto Video- 🤍 definitely go check out that one above after this video. Check out these video's below if you are interested in Naruto content. Link to my Kakuzu video- 🤍 Link to my Madara video- 🤍
What is Bias? What is the tradeoff between bias and variance? These questions and more answered today! ABOUT ME ⭕ Subscribe: 🤍 📚 Medium Blog: 🤍 💻 Github: 🤍 👔 LinkedIn: 🤍 RESOURCES  What are estimators? 🤍  The importance of Mean Squared Error and it's bias-variance decomposition: 🤍  Unbiased Estimators: 🤍  Bias Variance Tradeoff: 🤍 [X] More resources on bias-variance decomposition: 🤍 MATH COURSES (7 day free trial) 📕 Mathematics for Machine Learning: 🤍 📕 Calculus: 🤍 📕 Statistics for Data Science: 🤍 📕 Bayesian Statistics: 🤍 📕 Linear Algebra: 🤍 📕 Probability: 🤍 OTHER RELATED COURSES (7 day free trial) 📕 ⭐ Deep Learning Specialization: 🤍 📕 Python for Everybody: 🤍 📕 MLOps Course: 🤍 📕 Natural Language Processing (NLP): 🤍 📕 Machine Learning in Production: 🤍 📕 Data Science Specialization: 🤍 📕 Tensorflow: 🤍
Web and Society: Bias Anjalie Field, Chan Young Park, Kevin Lin and Yulia Tsvetkov: Controlled Analyses of Social Biases in Wikipedia Bios Friday 29/04/2022 - 11h30-13h00 CEST
This is an audio version of the Wikipedia Article: 🤍 00:00:58 1 Definition 00:02:56 2 Examples 00:03:25 2.1 Sample variance 00:17:08 2.2 Estimating a Poisson probability 00:19:06 2.3 Maximum of a discrete uniform distribution 00:20:04 3 Median-unbiased estimators 00:21:03 4 Bias with respect to other loss functions 00:22:02 5 Effect of transformations 00:23:01 6 Bias, variance and mean squared error 00:24:59 6.1 Example: Estimation of population variance 00:26:27 7 Bayesian view 00:27:26 8 See also 00:31:21 9 Notes 00:32:20 10 References Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: 🤍 Other Wikipedia audio articles at: 🤍 Upload your own Wikipedia articles through: 🤍 Speaking Rate: 0.8491775158449761 Voice name: en-GB-Wavenet-A "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY = In statistics, the bias (or bias function) of an estimator is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called unbiased. In statistics, "bias" is an objective property of an estimator. Unlike the ordinary English use of the term "bias", it is not pejorative even though it's not a desired property. Bias can also be measured with respect to the median, rather than the mean (expected value), in which case one distinguishes median-unbiased from the usual mean-unbiasedness property. Bias is related to consistency in that consistent estimators are convergent and asymptotically unbiased (hence converge to the correct value as the number of data points grows arbitrarily large), though individual estimators in a consistent sequence may be biased (so long as the bias converges to zero); see bias versus consistency. All else being equal, an unbiased estimator is preferable to a biased estimator, but in practice biased estimators are frequently used, generally with small bias. When a biased estimator is used, bounds of the bias are calculated. A biased estimator may be used for various reasons: because an unbiased estimator does not exist without further assumptions about a population or is difficult to compute (as in unbiased estimation of standard deviation); because an estimator is median-unbiased but not mean-unbiased (or the reverse); because a biased estimator gives a lower value of some loss function (particularly mean squared error) compared with unbiased estimators (notably in shrinkage estimators); or because in some cases being unbiased is too strong a condition, and the only unbiased estimators are not useful. Further, mean-unbiasedness is not preserved under non-linear transformations, though median-unbiasedness is (see § Effect of transformations); for example, the sample variance is an unbiased estimator for the population variance, but its square root, the sample standard deviation, is a biased estimator for the population standard deviation. These are all illustrated below.
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How does Bias ruin your research? (It probably doesn't, but sounds better this way!) And how do we avoid it? Tune in to find out! Resources used: Bordens, K. S., & Abbott, B. B. (2002). Research design and methods: A process approach. McGraw-Hill. Preece, J., Sharp, H., & Rogers, Y. (2015). Interaction design: beyond human-computer interaction. John Wiley & Sons. Beery, T. A. (1995). Gender bias in the diagnosis and treatment of coronary artery disease. Heart & Lung: The Journal of Cardiopulmonary and Acute Care, 24(6), 427-435. Choi, B. C., & Pak, A. W. (2005). A catalog of biases in questionnaires. Preventing chronic disease, 2(1), A13. Pannucci, C. J., & Wilkins, E. G. (2010). Identifying and avoiding bias in research. Plastic and reconstructive surgery, 126(2), 619–625. Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world?. The Behavioral and brain sciences, 33(2-3), 61–135. 🤍 🤍 🤍 🤍 🤍
This is an audio version of the Wikipedia Article: 🤍 00:01:34 1 Overview 00:04:07 2 Types 00:07:09 2.1 List of biases 00:07:24 3 Practical significance 00:08:53 4 Reducing 00:11:52 5 Common theoretical causes of some cognitive biases 00:14:33 6 Individual differences in decision-making biases 00:15:26 7 Criticisms Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: 🤍 Other Wikipedia audio articles at: 🤍 Upload your own Wikipedia articles through: 🤍 Speaking Rate: 0.9430377868630916 Voice name: en-US-Wavenet-B "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY = A cognitive bias is a systematic pattern of deviation from norm or rationality in judgment. Individuals create their own "subjective social reality" from their perception of the input. An individual's construction of social reality, not the objective input, may dictate their behaviour in the social world. Thus, cognitive biases may sometimes lead to perceptual distortion, inaccurate judgment, illogical interpretation, or what is broadly called irrationality.Some cognitive biases are presumably adaptive. Cognitive biases may lead to more effective actions in a given context. Furthermore, allowing cognitive biases enable faster decisions which can be desirable when timeliness is more valuable than accuracy, as illustrated in heuristics. Other cognitive biases are a "by-product" of human processing limitations, resulting from a lack of appropriate mental mechanisms (bounded rationality), or simply from a limited capacity for information processing.A continually evolving list of cognitive biases has been identified over the last six decades of research on human judgment and decision-making in cognitive science, social psychology, and behavioral economics. Kahneman and Tversky (1996) argue that cognitive biases have efficient practical implications for areas including clinical judgment, entrepreneurship, finance, and management.
Confirmation bias is a tendency to look for, interpret, and recall information in ways that affirm our preconception. Whenever we encounter objective facts on an issue we look at them through the lens of our own beliefs. As a result, we see and overrate where the two intercept. The bias is strongest for emotionally charged issues or when we search for desired outcomes. This joke illustrates it quite well... Subscribe to: 🤍 A special thank you to our patrons: Avigail, Badrah, Cedric Wang, David Markham, Denis Kraus, Don Bone, Esther Chiang, Eva Marie Koblin, John Zhang, Julien Dumesnil, Mathis Nu, and all the others!!! You keep us going! If you want to join us, visit 🤍 Read the entire script here: 🤍 SOURCES: 🤍 🤍 🤍 🤍 Classroom activity: 🤍 Subscribe to: 🤍
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SOURCE GUIDE 1) Confirmation Bias [🤍 2) Confirmation Bias And The Power Of Disconfirming Evidence [🤍 3) Doubt is essential for science - but for politicians its a sign of weakness [🤍 4) Scientist Thinking vs Lawyer Thinking 🤍 5) Intellectual Humility: The Importance Of Knowing You Might Be Wrong [🤍 6) Humans are hardwired to dismiss facts that don’t fit their worldview [🤍 7) Digital Media Literacy: What Is An Echo Chamber [🤍 8) Biased Make People Vulnerable To Misinformation Spread By Social Media [🤍 9) Coronavirus: Youtube Tightens Rules After David Icke 5G Video [🤍 10) Coronavirus: Facebook will start warning users who engaged with harmful misinformation [🤍 11) Facts, beliefs and identity: The Seeds Of Science Of Skepticism [🤍 12) Anomaly Hunting [🤍 13) Patternicity: Finding Meaningful Patterns In Meaningless Noise [🤍 14) Apophenia: Pattern: Does everything really happen for a reason [🤍 15) The Umbrella Man [🤍 16) Assassination Of John F Kennedy [🤍 17) JFK Assassination: Why suspicious still linger about The Umbrella Man [🤍 18) The Historical Society: Umbrella Man [🤍 19) Anomaly Hunting And The Umbrella Man [🤍 20) Umbrella Man (JFK Assassination) [🤍 21) 9/11 Debunked: BBC Early Report on WTC7 Collapse Explained [🤍 22) The BBC’s ‘WTC7 Collapsed at 4.54 [🤍 23) Chief of Department FDNY (ret.) Daniel Nigro Addresses Conspiracy Theories [🤍 24) BBC - The Editors: Part of the conspiracy? (2) [🤍
Everyone uses Wikipedia in their day-to-day lives, but there is a massive issue with its gender bias. 90% of editors are male, and of the total biographies on English Wikipedia only 18% are about women. Join Lucy from Leeds Museums & Galleries to discuss this bias, how it affects the information we receive and learn some simple steps to start to tackle gender bias on the sixth most popular website in the world. Local and Family History Librarian Manager, Louise Birch shares Womens History resources available at Leeds Libraries. leeds.gov.uk/leisure/libraries
We are going to be explaining 12 cognitive biases in this video and presenting them in a format that you can easily understand to help you make better decision in your life. Cognitive biases are flaws in logical thinking that clear the path to bad decisions, so learning about these ideas can reduce errors in your thought process, leading to a more successful life. These biases are very closely related to logical fallacies, which may help you win an argument or present information better. Ismonoff: 🤍 1)Anchoring Bias 2)Availability Heuristic bias 3)Bandwagon Bias 4)Choice Supportive Bias 5)Confirmation Bias 6)Ostrich Bias 7)Outcome Bias 8)Overconfidence 9)Placebo bias 10)Survivorship Bias 11)Selective Perception Bias 12)Blind Spot Bias What I make my videos with: 🤍 Insta: 🤍 Twitter: 🤍 Facebook: 🤍 Check out MY Passive Income Ebook: 🤍
Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs or values. People display this bias when they select information that supports their views, ignoring contrary information, or when they interpret ambiguous evidence as supporting their existing attitudes. The effect is strongest for desired outcomes, for emotionally charged issues, and for deeply entrenched beliefs. Confirmation bias cannot be eliminated, but it can be managed, for example, by education and training in critical thinking skills. Biased search for information, biased interpretation of this information, and biased memory recall, have been invoked to explain four specific effects: (1) attitude polarization (when a disagreement becomes more extreme even though the different parties are exposed to the same evidence), (2) belief perseverance (when beliefs persist after the evidence for them is shown to be false), (3) the irrational primacy effect (a greater reliance on information encountered early in a series), and (4) illusory correlation (when people falsely perceive an association between two events or situations). A series of psychological experiments in the 1960s suggested that people are biased toward confirming their existing beliefs. Later work re-interpreted these results as a tendency to test ideas in a one-sided way, focusing on one possibility and ignoring alternatives. In general, current explanations for the observed biases reveal the limited human capacity to process the complete set of information available, leading to a failure to investigate in a neutral, scientific way. Flawed decisions due to confirmation bias have been found in political, organizational, financial and scientific contexts. These biases contribute to overconfidence in personal beliefs and can maintain or strengthen beliefs in the face of contrary evidence. For example, confirmation bias produces systematic errors in scientific research based on inductive reasoning (the gradual accumulation of supportive evidence). Similarly, a police detective may identify a suspect early in an investigation, but then may only seek confirming rather than disconfirming evidence. A medical practitioner may prematurely focus on a particular disorder early in a diagnostic session, and then seek only confirming evidence. In social media, confirmation bias is amplified by the use of filter bubbles, or "algorithmic editing", which display to individuals only information they are likely to agree with, while excluding opposing views. ✅ ABOUT ▬▬▬▬▬▬▬▬▬▬▬▬▬ • My goal is to foster a community of learners with broad understandings. As someone who enjoys learning different things, I want to share my passion with you. • All topics are covered ranging from simple to complex. • Subscribe if you like to learn new things. ✅ CREDITS ▬▬▬▬▬▬▬▬▬▬▬▬▬ • Song: Fredji - Happy Life (Vlog No Copyright Music) Music provided by Vlog No Copyright Music. Video Link: 🤍 • This video uses material from the Wikipedia article Confirmation bias 🤍 which is released under the Creative Commons Attribution-Share-Alike License 3.0 🤍 • Images are used under one of the following: fair use, CC BY, CC BY-SA, CC BY-ND, CC BY-NC, CC BY-NC-SA, CC BY-NC-ND.
This is an audio version of the Wikipedia Article: 🤍 00:00:51 Reviews Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: 🤍 Other Wikipedia audio articles at: 🤍 Upload your own Wikipedia articles through: 🤍 Speaking Rate: 0.7853218328734716 Voice name: en-US-Wavenet-A "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY = Anthropic Bias: Observation Selection Effects in Science and Philosophy (2002) is a book by philosopher Nick Bostrom. Bostrom investigates how to reason when suspected that evidence is biased by "observation selection effects", in other words, evidence that has been filtered by the precondition that there be some appropriate positioned observer to "have" the evidence. This conundrum is sometimes hinted at as "the anthropic principle," "self-locating belief," or "indexical information". Discussed concepts include the self-sampling assumption and the self-indication assumption.
I look into the study called Demonstrations and Political Violence in America, and it is pretty biased. This study is known for stating that protests are mostly peaceful, particularly that 93% of protests are peaceful. I go through many of the specific examples it gives, from Micheal Brown, to Rashard Brooks, to Jacob Blake, and the study also covers the activities in Lafayette Square, CHAZ, and Portland. I think this study had some interesting data, and I appreciate having it, but considering the red flags I saw in this study, I still don’t think the term ‘mostly peaceful protests’ applies nearly as often as it is used. If you enjoyed this video, I would recommend this video on a deep dive into data on systemic racism: 🤍 Subscribe: 🤍 Sources: Peaceful Protest study: 🤍 FBI report on Micheal Brown: 🤍 Rayshard Brooks Summary: 🤍 Police side of Jacob Blake: 🤍 Statues removed or damaged during protests: 🤍 Fox on Lafayette: 🤍 Wikipedia on CHAZ: 🤍 Vox link to CHAZ/CHOP: 🤍 Andy Ngo footage of Portland: 🤍 BitChute Channel: 🤍 Discord: 🤍 Email: on.the.other.hand.videos🤍gmail.com