The Half-life of FactsWhy Everything We Know Has an Expiration Date
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Zusammenfassungen
New insights from the science of science Facts change all the time. Smoking has gone from doctor recommended to deadly. We used to think the Earth was the center of the universe and that Pluto was a planet. For decades, we were convinced that the brontosaurus was a real dinosaur. In short, what we know about the world is constantly changing. But it turns out there’s an order to the state of knowledge, an explanation for how we know what we know. Samuel Arbesman is an expert in the field of scientometricsliterally the science of science. Knowledge in most fields evolves systematically and predictably, and this evolution unfolds in a fascinating way that can have a powerful impact on our lives. Doctors with a rough idea of when their knowledge is likely to expire can be better equipped to keep up with the latest research. Companies and governments that understand how long new discoveries take to develop can improve decisions about allocating resources. And by tracing how and when language changes, each of us can better bridge generational gaps in slang and dialect. Just as we know that a chunk of uranium can break down in a measurable amount of timea radioactive half-lifeso too any given field’s change in knowledge can be measured concretely. We can know when facts in aggregate are obsolete, the rate at which new facts are created, and even how facts spread. Arbesman takes us through a wide variety of fields, including those that change quickly, over the course of a few years, or over the span of centuries. He shows that much of what we know consists of mesofacts”facts that change at a middle timescale, often over a single human lifetime. Throughout, he offers intriguing examples about the face of knowledge: what English majors can learn from a statistical analysis of The Canterbury Tales, why it’s so hard to measure a mountain, and why so many parents still tell kids to eat their spinach because it’s rich in iron.
The Half-life of Facts is a riveting journey into the counterintuitive fabric of knowledge. It can help us find new ways to measure the world while accepting the limits of how much we can know with certainty.
Dieses Buch erwähnt ...
![]() Personen KB IB clear | Dan Ariely , Isaac Asimov , Charles Babbage , Albert-László Barabási , Rodney Brooks , David Brooks , Bryan Caplan , Nicholas G. Carr , Clayton Christensen , Arthur C. Clarke , Tyler Cowen , Charles Darwin , Albert Einstein , Richard Feynman , Mark Granovetter , Johann Gutenberg , Joseph Henrich , John P. A. Ioannidis , Steven Johnson , Daniel Kahneman , Alan Kay , Kevin Kelly , John Maynard Keynes , Jon Kleinberg , Leibniz , Hod Lipson , Jenny Liu , Warren McCulloch , Stanley Milgram , Gordon Moore , Randall Munroe , Tom Murphy , Isaac Newton , Barack Obama , Derek de Solla Price , Carl Sagan , Clay Shirky , Herbert Simon , John Maynard Smith , Betsy Sparrow , Duncan J. Watts , Daniel M. Wegner | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
![]() Aussagen KB IB clear | Halbwertszeit des Fachwissens sinkt | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
![]() Begriffe KB IB clear | Bildungeducation (Bildung)
, Buchdruck printing press
, Categorization Categorization
, cognitive biascognitive bias
, confirmation bias
, Daten data
, elektrische Energie
, Gehirn brain
, Gesellschaft society
, Godwin’s Law
, h-index
, Impact FactorImpact Factor
, Informationinformation
, Innovation innovation
, Internet internet
, Klimawandel
, Kommunikation communication
, Kryptographiecryptography
, Long Tail Long Tail
, Maschine machine
, Mathematik mathematics
, Mendeley
, Metaanalysemeta-analysis
, Netzwerk network
, Paradigmaparadigm
, Produktivität productivity
, Programmieren programming
, Psychologie psychology
, Publikationsbiaspublication bias
, ScientometricsScientometrics
, self-serving biasself-serving bias
, Sprache language
, Statistik statistics
, Struktur structure
, Success to the SuccessfulSuccess to the Successful
, Theorietheory
, Twitter
, Wikipedia
, Wissenschaft science
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Dieses Buch erwähnt vermutlich nicht ... 
![]() Nicht erwähnte Begriffe | academia.edu, Digitalisierung, Effektstärke, facebook, Schule, Selbstüberschätzung |
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5 Erwähnungen 
- Thinking in bets - making smarter decisions when you don’t have all the facts (Annie Duke)

- Understanding beliefs (Nils Nilsson) (2014)

- Superforcasting - The Art and Science of Prediction (Philip E. Tetlock, Dan Gardner) (2015)

- Informational Environments - Effects of Use, Effective Designs (Jürgen Buder, Friedrich W. Hesse) (2017)

- 4. Motivated Processing of Health-Related Information in Online Environments (Joachim Kimmerle, Martina Bientzle, Ulrike Creß, Danny Flemming, Hannah Greving, Johannes Grapendorf et al.)

- 4. Motivated Processing of Health-Related Information in Online Environments (Joachim Kimmerle, Martina Bientzle, Ulrike Creß, Danny Flemming, Hannah Greving, Johannes Grapendorf et al.)
- Framers - Human Advantage in an Age of Technology and Turmoil (Kenneth Cukier, Viktor Mayer-Schönberger, Francis de Véricourt) (2021)

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Beat hat dieses Buch erst in den letzten 6 Monaten in Biblionetz aufgenommen. Er hat dieses Buch einmalig erfasst und bisher nicht mehr bearbeitet. Beat besitzt kein physisches, aber ein digitales Exemplar. (das er aber aus Urheberrechtsgründen nicht einfach weitergeben darf). Aufgrund der vielen Verknüpfungen im Biblionetz scheint er sich intensiver damit befasst zu haben. Es gibt bisher nur wenige Objekte im Biblionetz, die dieses Werk zitieren.

Buchdruck
Categorization
Daten
elektrische Energie
Gehirn
Gesellschaft
Innovation
Internet
Klimawandel
Kommunikation
Long Tail
Maschine
Mathematik
Netzwerk
Produktivität
Programmieren
Psychologie
Sprache
Statistik
Struktur
Twitter
Wikipedia
Wissenschaft














Biblionetz-History