Hasil untuk "Social Sciences"

Pierre Paillé, Alex Mucchielli, Hélène Ayotte et al.

Charles C. Ragin

E. Babbie

H. Bernard

K. Arrow

M. Crotty

B. Walker, C. S. Holling, S. Carpenter et al.

. The concept of resilience has evolved considerably since Holling’s (1973) seminal paper. Different interpretations of what is meant by resilience, however, cause confusion. Resilience of a system needs to be considered in terms of the attributes that govern the system’s dynamics. Three related attributes of social– ecological systems (SESs) determine their future trajectories: resilience, adaptability, and transformability. Resilience (the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks) has four components—latitude, resistance, precariousness, and panarchy—most readily portrayed using the metaphor of a stability landscape. Adaptability is the capacity of actors in the system to influence resilience (in a SES, essentially to manage it). There are four general ways in which this can be done, corresponding to the four aspects of resilience. Transformability is the capacity to create a fundamentally new system when ecological, economic, or social structures make the existing system untenable. The implications of this interpretation of SES dynamics for sustainability science include changing the focus from seeking optimal states and the determinants of maximum sustainable yield (the MSY paradigm), to resilience analysis, adaptive resource management, and adaptive governance.

James D. Thompson

J. Law

John Scott

This paper reports on the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work. It is argued that the concept of social network provides a powerful model for social structure, and that a number of important formal methods of social network analysis can be discerned. Social network analysis has been used in studies of kinship structure, social mobility, science citations, contacts among members of deviant groups, corporate power, international trade exploitation, class structure, and many other areas. A review of the formal models proposed in graph theory, multidimensional scaling, and algebraic topology is followed by extended illustrations of social network analysis in the study of community structure and interlocking directorships.

J. R. French, B. Raven

S. Cutter, B. Boruff, W. L. Shirley

M. Woolcock, D. Narayan

E. Babbie

K. Lewin

J. Epstein, R. Axtell

R. Putnam

A. Sayer

S. Jasanoff

T. Toivonen, V. Heikinheimo, Christoph Fink et al.

Abstract Improved understanding of human-nature interactions is crucial to conservation science and practice, but collecting relevant data remains challenging. Recently, social media have become an increasingly important source of information on human-nature interactions. However, the use of advanced methods for analysing social media is still limited, and social media data are not used to their full potential. In this article, we present available sources of social media data and approaches to mining and analysing these data for conservation science. Specifically, we (i) describe what kind of relevant information can be retrieved from social media platforms, (ii) provide a detailed overview of advanced methods for spatio-temporal, content and network analyses, (iii) exemplify the potential of these approaches for real-world conservation challenges, and (iv) discuss the limitations of social media data analysis in conservation science. Combined with other data sources and carefully considering the biases and ethical issues, social media data can provide a complementary and cost-efficient information source for addressing the grand challenges of biodiversity conservation in the Anthropocene epoch.