Search

The Quality & Quantity was established in 1967 and in 2017 it completed its half century. The journal is interdisciplinary in nature and it mainly discusses methodological application of mathematics and statistics in the social sciences, particularly sociology, economics, and social psychology. It was created with the idea of advancing methodology of the various social studies. This study looks back journey of the journal from 1967 to 2017 aims to develop a bibliometric analysis of all the publications of the journal. Web of Science Core Collection database is used to collect data. The present study discovered the significant contributions of the journal in terms of impact, topics, authors, universities and countries. Utrecht University of Netherlands is the most productive university. Asian Universities are emerging and growing quickly in the recent years. Although USA leads among the countries but Europe leads among the six supranational regions. Finally, the visualization of similarities viewer software is used to present network visualization of the bibliographic coupling, co-citation, citation, co-authorship and co-occurrence of keywords. [ABSTRACT FROM AUTHOR]

This essay proposes a historical reconstruction in three phases of the relationship between sociology and mathematics: (a) P.F. Lazarfeld's choices regarding theory, methodology and mathematics within the objectivity paradigm; (b) the relationship between mathematics and sociology, from statistic models and artificial societies to social simulation; (c) the new possibilities that Artificial Neural Networks offer sociology. [ABSTRACT FROM AUTHOR]

The article discusses issues concerning the social condition of Mapuche Indians. Issues concerning the intercultural relations and the practice of traditional medicine in Mapuche societies are discussed. History and origin of Mapuche Indians are also discussed. Role played by the NGO Nexus Emilia Romagna in promoting international cooperation for the betterment of the quality of life of Mapuche people is highlighted.

Copyright of Inchiesta is the property of Edizioni Dedalo SRL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revue Française de Sociologie is the property of Presses de Sciences Po and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of the article is to demonstrate how entropy and some theorems of the theory of information may be useful in the domain of classification, both for class formation and for class identification. Starting from a sample of subjects who have given different answers to a battery of tests or items, researchers see that there can be two kinds of approaches. Firstly, on the basis of entropy one can sort out the tests that have higher information content and on this basis form classes of subjects whose homogeneity can be appraised. In this case the problem is therefore to form a certain number of homogeneous classes with the minimum number of tests. Secondly, once the classification of subjects has been made, it is possible, according to the theory of information, to see whether the typical sequence of subjects of the different classes can be established also through fewer tests, being it then possible also to recognize a distance between the different classes. With this method researchers try to arrive at homogeneous classes on the basis of the smallest possible number of tests, that is in effect choosing variables with the greatest discriminating power.