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.


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


Twitter: frbailo




  • easyMTS: My First R Package (Story, and Results)
    This weekend I decided to create my first R package… it’s here! Although I’ve been using R for 15 years, developing a package has been the one thing slightly out of reach for me. Now that I’ve been through the process once, with a package that’s not completely done (but at least has a […]
  • easyMTS R Package: Quick Solver for Mahalanobis-Taguchi System (MTS)
    A new R package in development. Please cite if you use it. The post easyMTS R Package: Quick Solver for Mahalanobis-Taguchi System (MTS) appeared first on Quality and Innovation.
  • Hyper-Parameter Optimization of General Regression Neural Networks
    A major advantage of General Regression Neural Networks (GRNN) over other types of neural networks is that there is only a single hyper-parameter, namely the sigma. In the previous post (, I’ve shown how to use the random search strategy to find a close-to-optimal value of the sigma by using various random number generators, including […]
  • Cluster multiple time series using K-means
    I have been recently confronted to the issue of finding similarities among time-series and though about using k-means to cluster them. To illustrate the method, I’ll be using data from the Penn World Tables, readily available in R (inside the {pwt9} package): library(tidyverse) library(lubridate) library(pwt9) library(brotools) First, of all, let’s only select the needed columns: […]
  • A Shiny Intro Survey to an Open Science Course
    Last week, we started a new course titled “Statistical Programming and Open Science Methods”. It is being offered under the research program of TRR 266 “Accounting for Transparency” and enables students to conduct data-based research so that...

RSS Simply Statistics

  • 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 […]
  • The data deluge means no reasonable expectation of privacy - now what?
    Today a couple of different things reminded me about something that I suppose many people are talking about but has been on my mind as well. The idea is that many of our societies social norms are based on the reasonable expectation of privacy. But the reasonable expectation of privacy is increasingly a thing of […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • When presenting a new method, talk about its failure modes.
    A coauthor writes: I really like the paper [we are writing] as it is. My only criticism of it perhaps would be that we present this great new method and discuss all of its merits, but we do not really discuss when it fails / what its downsides are. Are there any cases where the […]
  • The best is the enemy of the good. It is also the enemy of the not so good.
    This post is by Phil Price, not Andrew. The Ocean Cleanup Project’s device to clean up plastic from the Great Pacific Garbage Patch is back in the news because it is back at work and is successfully collecting plastic. A bunch of my friends are pretty happy about it and have said so on social […]
  • On the term “self-appointed” . . .
    I was reflecting on what bugs me so much about people using the term “self-appointed” (for example, when disparaging “self-appointed data police” or “self-appointed chess historians“). The obvious question when someone talks about “self-appointed” whatever is, Who self-appointed you to decide who is illegitimately self-appointed? But my larger concern is with the idea that being […]