The introduction of fuzzy-sets into social science has potentially improved our ability to study diversity by means of the so-called partial memberships. As a consequence, social phenomena can be studied empirically as a matter of degree and not longer as fixed types. A fuzzy-set is a set with elements whose membership grades can have any real value between 0 and 1. In order to illustrate the capacities of the fuzzy set logic and also to make the discussion less abstract, it will be applied to the study of welfare state reforms. The ‘grading capacity’ of fuzzy-sets makes it possible to study welfare states as partial members of different welfare state regimes at the same time. This approach reveals the diversity of welfare reforms better than traditional ways which are often inclined to picture a case as representative of one particular type which is a too crude classification. Fuzzy-sets are designed to capture the diversity in a way that leaves more room to map individual cases without falling into the trap of idiosyncrasy. An equally important ability of fuzzy-sets is to analyse causal relationships in a small-n design. The fuzzy-set logic can be used to determine necessary and sufficient conditions for an outcome. This takes the form of expressions which reveal multiple-conjunctural causation patterns. In this paper the conditions for welfare cutbacks and the effects on socio-economic performance will be examined.
Quality & Quantity – Springer Journals
Published: Oct 20, 2004
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
All the latest content is available, no embargo periods.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud