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Open source tool can help identify gerrymandering in voting maps | WSU Insider


May 6, 2021
By Sara Zaske, WSU News
PULLMAN, Wash. With state legislatures nationwide preparing for the once-a-decade redrawing of voting districts, a research team has developed a better computational method to help identify improper gerrymandering designed to favor specific candidates or political parties.
In an article in the Harvard Data Science Review, the researchers describe the improved mathematical methodology of an open source tool called GerryChain. The tool can help observers detect gerrymandering in a voting district plan by creating a pool, or ensemble, of alternate maps that also meet legal voting criteria. This map ensemble can show if the proposed plan is an extreme outlier one that is very unusual from the norm of plans generated without bias, and therefore, likely to be drawn with partisan goals in mind. ....

United States , Sara Zaske , Daryl Deford , Washington State University , Massachusetts Institute Of Technology , Department Of Mathematics , Voting Rights Data Institute , Tufts University , Harvard Data Science Review , Virginia House , Rights Data Institute , Moon Duchin , Justin Solomon , Massachusetts Institute , Voting Rights Act , Media Relations , ஒன்றுபட்டது மாநிலங்களில் , டேரில் டெபோர்ட , வாஷிங்டன் நிலை பல்கலைக்கழகம் , மாசசூசெட்ஸ் நிறுவனம் ஆஃப் தொழில்நுட்பம் , துறை ஆஃப் கணிதம் , டஃப்ட்ஸ் பல்கலைக்கழகம் , ஹார்வர்ட் தகவல்கள் அறிவியல் விமர்சனம் , வர்ஜீனியா வீடு , ஜஸ்டின் சாலமன் , மாசசூசெட்ஸ் நிறுவனம் ,

Open source tool can help identify gerrymandering in voting maps


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IMAGE: Visualization of sampled county-preserving Virginia Congressional voting districts, created with the ReCom method in Gerrychain.
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Credit: Daryl DeFord, Washington State University
PULLMAN, Wash. With state legislatures nationwide preparing for the once-a-decade redrawing of voting districts, a research team has developed a better computational method to help identify improper gerrymandering designed to favor specific candidates or political parties.
In an article in the Harvard Data Science Review, the researchers describe the improved mathematical methodology of an open source tool called GerryChain. The tool can help observers detect gerrymandering in a voting district plan by creating a pool, or ensemble, of alternate maps that also meet legal voting criteria. This map ensemble can show if the proposed plan is an extreme outlier one that is very unusual from the norm of plans generated without bias, and therefore, likely ....

United States , Daryl Deford , Washington State University , Massachusetts Institute Of Technology , Voting Rights Data Institute , Tufts University , Harvard Data Science Review , Virginia House , Rights Data Institute , Moon Duchin , Justin Solomon , Massachusetts Institute , Voting Rights Act , ஒன்றுபட்டது மாநிலங்களில் , டேரில் டெபோர்ட , வாஷிங்டன் நிலை பல்கலைக்கழகம் , மாசசூசெட்ஸ் நிறுவனம் ஆஃப் தொழில்நுட்பம் , டஃப்ட்ஸ் பல்கலைக்கழகம் , ஹார்வர்ட் தகவல்கள் அறிவியல் விமர்சனம் , வர்ஜீனியா வீடு , ஜஸ்டின் சாலமன் , மாசசூசெட்ஸ் நிறுவனம் , வாக்களித்தல் உரிமைகள் நாடகம் ,

Why machine learning, not artificial intelligence, is the right way forward for data science


Why machine learning, not artificial intelligence, is the right way forward for data science
on April 5, 2021, 1:59 PM PST
Commentary: We like to imagine an AI-driven future, but it s machine learning that will actually help us to progress, argues expert Michael I. Jordan.
Image: iStock/Igor Kutyaev
We bandy about the term artificial intelligence, evoking ideas of creative machines anticipating our every whim, though the reality is more banal: For the foreseeable future, computers will not be able to match humans in their ability to reason abstractly about real-world situations. This is from Michael I. Jordan, one of the foremost authorities on AI and machine learning, who wants us to get real about AI. ....

Igor Kutyaev , Zdnet Techrepublic , Harvard Data Science Review , Techrepublic Premium , Harvard Data Science , ஹார்வர்ட் தகவல்கள் அறிவியல் விமர்சனம் , ஹார்வர்ட் தகவல்கள் அறிவியல் ,

Harvard Data Science Review explores reproducibility and replicability in science


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CAMBRIDGE, MA December 16, 2020 In 2019, the National Academies of Science, Engineering, and Medicine (NASEM) published a consensus report for the US Congress Reproducibility and Replicability in Science which addressed a major methodological crisis in the sciences: The fact that many experiments and results are difficult or impossible to reproduce. The conversation about this report and this vital topic continues in a special, twelve-article feature in issue 2:4 of the
Growing awareness of the replication crisis has rocked the fields of medicine and psychology, in particular, where famous experiments and influential findings have been cast into doubt. But these issues affect researchers in a wide range of disciplines from economics to particle physics to climate science and addressing them requires an interdisciplinary approach. ....

United Kingdom , City Of , Amy Harris , National Academies Of Science , Harvard Data Science Initiative , Knowledge Futures Group , Victoria Stodden University Of Illinois , Media Lab , National Academies , Harvard Data Science Review , Chief Xiao Li Meng , Victoria Stodden , ஒன்றுபட்டது கிஂக்டம் , நகரம் ஆஃப் , ஆமி ஹாரிஸ் , ஹார்வர்ட் தகவல்கள் அறிவியல் முயற்சி , அறிவு எதிர்காலங்கள் குழு , விக்டோரியா ஸ்டொட்டேன் பல்கலைக்கழகம் ஆஃப் இல்லினாய்ஸ் , மீடியா ஆய்வகம் , ஹார்வர்ட் தகவல்கள் அறிவியல் விமர்சனம் , தலைமை கிஷியஓ லி மெங் , விக்டோரியா ஸ்டொட்டேன் ,