Cosa possiamo imparare dal M5S

Leggo e rispondo al post di Massimo Mantellini (Il M5S, il wifi e il principio di precauzione) in cui si evidenzia con preoccupazione come il Movimento abbia portato in Parlamento, dunque in qualche modo legittimandole, posizioni anti-scientifiche; un “pensiero tossico, banale e a suo modo inattaccabile, che nuoce al Paese intero”.

Il Movimento Cinque Stelle con un bacino elettorale che si aggira tra il 25 e il 30% (8.5-10 milioni di persone) è necessariamente complesso in termini di rappresentanza demografica e di diversità di opinione. Considerando un astensionismo del 25%, se vi trovate in fila al supermercato delle 10 persone che vi precedono circa due votano M5S. Purtroppo questa complessità raramente traspare nelle narrazioni giornalistiche, e chi fa informazione tende (troppo) spesso a preferire i tratti caricaturali (da cappello di carta stagnola o da gita in Corea del Nord, per intenderci). Ma questo tipo di informazione è sbagliata: primo perché distorce nella semplificazione, secondo perché incoraggia comportamenti macchiettistici, grotteschi e sbracati da parte di chi sedendo in istituzioni affollate cerca visibilità.

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Friday, 22 July 2016

Road to Rome: The organisational and political success of the M5S

The Five Star Movement (M5S) obtained two major victories in the second round of municipal elections on 19 June 2016 in Rome and Turin. Rome attracted the most international attention but it is M5S’ victory in Turin that is likely the most consequential for them and other European anti-establishment parties.

In Rome, a municipality with 2.8 million people and an annual budget of €5 billon, Virginia Raggi (age 37) gained doubled the votes of her contender Roberto Giachetti (age 55). In Turin, a city with a population of 900,000 and an annual budget of €1.69 billion, Chiara Appendino (age 31) outstripped Piero Fassino (age 66) by about 10 percentage points.

Continue reading on Pop Politics Aus

Friday, 8 July 2016

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RSS r-bloggers.com

  • R Package for @racently
    I recently wrote about an API for @racently. The next logical step was to build a package which wraps the API so that the data can easily be pulled into R. The package is available here. It is still very much a work in progress: the API only exposes two endpoints, but both of them […]
  • celebRation 2020
    The year 2020 marks the 20th anniversary of the release of R version 1.0.0! To celebrate this, we are inviting the community of R users and developers for a two-day celebRation workshop/mini-conference on February 28-29th 2020 in Copenhagen. We kick off on 28th February with hands-on workshops on two hot topics, namely data visualization using […]
  • Practical Data Science with R 2nd Edition now in-stock at Amazon.com!
    Practical Data Science with R 2nd Edition is now in-stock at Amazon.com! Buy it for your favorite data scientist in time for the holidays!
  • lintools 0.1.3 is on CRAN
    Version 0.1.3 of the lintools package was accepted on CRAN today. This version brings a few internal improvements and switches the testing suite to the tinytest test infrastructure. lintools is provides basic manipulations of linear systems of equalities and inequalities … Continue reading →
  • Sponsorship: SatRdays and useR Groups
    SatRdays SatRdays are great. Low cost R events, held around the world. What's not to love! For the last year, we have been offering automatic sponsorship for all SatRday events. All the organisers have to do is complete a quick questionnaire and the money is sent on it's way. So far we have sponsored seven […]

RSS Simply Statistics

  • Is Artificial Intelligence Revolutionizing Environmental Health?
    NOTE: This post was written by Kevin Elliott, Michigan State University; Nicole Kleinstreuer, National Institutes of Health; Patrick McMullen, ScitoVation; Gary Miller, Columbia University; Bhramar Mukherjee, University of Michigan; Roger D. Peng, Johns Hopkins University; Melissa Perry, The George Washington University; Reza Rasoulpour, Corteva Agriscience, and Elizabeth Boyle, National Academies of Sciences, Engineering, and Medicine. […]
  • You can replicate almost any plot with R
    Although R is great for quickly turning data into plots, it is not widely used for making publication ready figures. But, with enough tinkering you can make almost any plot in R. For examples check out the flowingdata blog or the Fundamentals of Data Visualization book. Here I show five charts from the lay press […]
  • So You Want to Start a Podcast
    Podcasting has gotten quite a bit easier over the past 10 years, due in part to improvements to hardware and software. I wrote about both how I edit and record both of my podcasts about 2 years ago and, while not much has changed since then, I thought it might be helpful if I organized […]

RSS Statistical Modeling, Causal Inference, and Social Science