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

tweets


Twitter: frbailo

links


blogroll


RSS r-bloggers.com

  • r/finance, 1 year later
    The prominent conference R/Finance, held annually in Chicago, had a great program yesterday and today. As I wrote following last year’s conference, the organizers were criticized for including no women in its speaker lineup. The problem was that no women had submitted papers for consideration; no input, thus no output. I’m a member of the […]
  • A new package for panel data analysis in R
    It has been a long time coming, but my R package panelr is now on CRAN. Since I started work on it well over a year ago, it has become essential to my own workflow and I hope it can be useful for others. panel_data object class One key contribution, that I hope can help […]
  • The never-ending editor war (?)
    The creation of this blog post was prompted by this tweet, asking an age-old question: @spacemacs— Bruno Rodrigues (@brodriguesco) May 16, 2019 This is actually a very important question, that I have been asking myself for a long time. An IDE, and plain text editors, are a very important tools to anyone writing code. Most […]
  • Earthquake Analysis (4/4): Cluster Analysis
    Are you interested in guest posting? Publish at DataScience+ directly from your editor (i.e., RStudio). Category Basic Statistics Tags Data Visualisation Maps R Programming This is the fourth part of our post series about the exploratory analysis of a publicly available dataset reporting earthquakes and similar events within a specific 30 days time span. In […]
  • Mapping Tornado Alley with R
    I caught a re-tweet of this tweet by @harry_stevens: THREAD: I wrote a post on @observablehq about a map I made today. It shows a typical day in the life of a graphics journalist: You never know what problems you'll have to solve on deadline! https://t.co/yRhW1wbLxN #d3js #dataviz 1/7 pic.twitter.com/7N6mmK0nz3 — Harry Stevens (@Harry_Stevens) May... […]

RSS Simply Statistics

  • Generative and Analytical Models for Data Analysis
    Describing how a data analysis is created is a topic of keen interest to me and there are a few different ways to think about it. Two different ways of thinking about data analysis are what I call the “generative” approach and the “analytical” approach. Another, more informal, way that I like to think about […]
  • Tukey, Design Thinking, and Better Questions
    Roughly once a year, I read John Tukey’s paper “The Future of Data Analysis”, originally published in 1962 in the Annals of Mathematical Statistics. I’ve been doing this for the past 17 years, each time hoping to really understand what it was he was talking about. Thankfully, each time I read it I seem to […]
  • Interview with Abhi Datta
    Editor’s note: This is the next in our series of interviews with early career statisticians and data scientists. Today we are talking to Abhi Datta about his work in large scale spatial analysis and his interest in soccer! Follow him on Twitter at @datta_science. If you have recommendations of an (early career) person in academics […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • Vigorous data-handling tied to publication in top journals among public heath researchers
    Gur Huberman points us to this news article by Nicholas Bakalar, “Vigorous Exercise Tied to Macular Degeneration in Men,” which begins: A new study suggests that vigorous physical activity may increase the risk for vision loss, a finding that has surprised and puzzled researchers. Using questionnaires, Korean researchers evaluated physical activity among 211,960 men and […]
  • Hey, people are doing the multiverse!
    Elio Campitelli writes: I’ve just saw this image in a paper discussing the weight of evidence for a “hiatus” in the global warming signal and immediately thought of the garden of forking paths. From the paper: Tree representation of choices to represent and test pause-periods. The ‘pause’ is defined as either no-trend or a slow-trend. […]
  • Data quality is a thing.
    I just happened to come across this story, where a journalist took some garbled data and spun a false tale which then got spread without question. It’s a problem. First, it’s a problem that people will repeat unjustified claims, also a problem that when data are attached, you can get complete credulity, even for claims […]