001448235 000__ 03507cam\a2200529\i\4500
001448235 001__ 1448235
001448235 003__ OCoLC
001448235 005__ 20230310004228.0
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001448235 008__ 220719s2022\\\\sz\a\\\\ob\\\\001\0\eng\d
001448235 019__ $$a1334888216
001448235 020__ $$a9783031019197$$q(electronic bk.)
001448235 020__ $$a3031019199$$q(electronic bk.)
001448235 020__ $$z9783031018336
001448235 020__ $$z3031018338
001448235 0247_ $$a10.1007/978-3-031-01919-7$$2doi
001448235 035__ $$aSP(OCoLC)1336595148
001448235 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCF$$dOCLCQ
001448235 049__ $$aISEA
001448235 050_4 $$aQ295
001448235 08204 $$a003$$223/eng/20220719
001448235 1001_ $$aBarbrook-Johnson, Pete,$$eauthor.
001448235 24510 $$aSystems mapping :$$bhow to build and use causal models of systems /$$cPete Barbrook-Johnson, Alexandra S. Penn.
001448235 264_1 $$aCham, Switzerland :$$bPalgrave Macmillan,$$c2022.
001448235 300__ $$a1 online resource :$$billustrations (black and white, and color).
001448235 336__ $$atext$$btxt$$2rdacontent
001448235 337__ $$acomputer$$bc$$2rdamedia
001448235 338__ $$aonline resource$$bcr$$2rdacarrier
001448235 504__ $$aIncludes bibliographical references and index.
001448235 5050_ $$aChapter 1: Introduction -- Chapter 2: Rich Pictures -- Chapter 3:Theory of Change diagrams -- Chapter 4: Causal Loop Diagrams -- Chapter 5: Participatory Systems Mapping -- Chapter 6: Fuzzy Cognitive Mapping -- Chapter 7: Bayesian Belief Networks -- Chapter 8: System Dynamics -- Chapter 9: What data and evidence can you build system maps from? -- Chapter 10: Running systems mapping workshops -- Chapter 11: Comparing, choosing, and combining systems mapping methods -- Chapter 12: Conclusion.
001448235 506__ $$aAccess limited to authorized users.
001448235 520__ $$aThis open access book explores a range of new and older systems mapping methods focused on representing causal relationships in systems. In a practical manner, it describes the methods and considers the differences between them; describes how to use them yourself; describes how to choose between and combine them; considers the role of data, evidence, and stakeholder opinion; and describes how they can be useful in a range of policy and research settings. This book provides a key starting point and general-purpose resource for understanding complex adaptive systems in practical, actionable, and participatory ways. The book successfully meets the growing need in a range of social, environmental, and policy challenges for a richer more nuanced, yet actionable and participatory understanding of the world. The authors provide a clear framework to alleviate any confusion about the use of appropriate terms and methods, enhance the appreciation of the value they can bring, and clearly explain the differences between approaches and the resulting outputs of mapping processes and analysis.
001448235 588__ $$aDescription based on print version record.
001448235 650_0 $$aSystem theory.
001448235 650_0 $$aCausation.
001448235 650_0 $$aSocial sciences$$xMathematical models.
001448235 650_0 $$aSocial sciences$$xStatistical methods.
001448235 655_0 $$aElectronic books.
001448235 7001_ $$aPenn, Alexandra S.,$$eauthor.
001448235 77608 $$iPrint version:$$aBarbrook-Johnson, Pete.$$tSystems mapping.$$dBasingstoke : Palgrave Macmillan, 2022$$z9783031018336$$w(OCoLC)1328010223
001448235 852__ $$bebk
001448235 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-01919-7$$zOnline Access$$91397441.1
001448235 909CO $$ooai:library.usi.edu:1448235$$pGLOBAL_SET
001448235 980__ $$aBIB
001448235 980__ $$aEBOOK
001448235 982__ $$aEbook
001448235 983__ $$aOnline
001448235 994__ $$a92$$bISE