Malfattori: Government Repression and Anarchist Violence

Author(s):  
Nunzio Pernicone ◽  
Fraser M. Ottanelli

Chapter 2 explains the role of government repression as the primary precipitant of Italian anarchist violence. Specifically it describes how, in a climate of growing economic hardship and social unrest among the peasantry and factory workers, in 1878 Giovanni Passanante’s failed “tyrannicide” of King Umberto I provided Italian authorities with a justification to attempt to deliver a mortal blow to socialism and the International. Repression took various forms. Socialists and anarchists groups were dissolved, their newspapers suppressed, rank-and-file members classified as “malefactors” and subjected to ammonizione (admonishment) and domicilio coatto (internal exile). Important anarchists were arrested and those who escaped detention, as in the case of Errico Malatesta and Carlo Cafiero, forced into exile. These developments led many anarchists to embrace anti-organizational forms of revolutionary ideology and practices that rejected all forms of organization and exalted terrorist violence.

2007 ◽  
pp. 80-92
Author(s):  
A. Kireev

The paper studies the problem of raiders activity on the market for corporate control. This activity is considered as a product of coercive entrepreneurship evolution. Their similarities and sharp distinctions are shown. The article presents the classification of raiders activity, discribes its basic characteristics and tendencies, defines the role of government in the process of its transformation.


1990 ◽  
Author(s):  
Odin Knudsen ◽  
John Nash ◽  
James Bovard ◽  
Bruce Gardner ◽  
L. Alan Winters
Keyword(s):  

2020 ◽  
Vol 4 (3) ◽  
pp. 247
Author(s):  
Dwi Swasono Rachmad

<p><em>H</em><em>ousing is derived from the word house</em><em> which means</em><em> a place that has a place to live which will stay or stop in a certain time. Housing is a residence that has been grouped into a place that has facilities and infrastructure. The problem in this study focuses on the type of residential ownership in the form of SHM ART, SHM Non ART, NON SHM and others. </em><em>T</em><em>hese four types</em><em> can be used</em><em> to know the percentage of ownership in all provinces in Indonesia. Due to the fact that there is still a lot of information about the type of certificate ownership, there is still not much ownership. Therefore, the use of the k-Means algorithm as a data mining concept in the form of clusters, where the data already has parameters or values that fall into the category of unsupervised learning. That data produced the best. The data was obtained from published sources of the Republic of Indonesia government agency, namely the Central Statistics Agency data with the category of household processing with self-owned residential buildings purchased from developers or non-developers by province and type of ownership in 2016 throughout Indonesia. In conducting the dataset, researchers used the RapidMiner application as a clustering process application. This research </em><em>shows that</em><em> there are more types of ownership in the SHM ART, but for other values it is still smaller than the value in other types of ownership which is the second largest value. So</em><em>,</em><em> in this case, the role of government in providing assistance in the process of ownership in order to become SHM ART</em><em> is very important</em><em>.</em></p>


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