CPD article: Understanding the social behaviour of dairy cattle can benefit welfare and productivity

Livestock ◽  
2020 ◽  
Vol 25 (5) ◽  
pp. 216-219
Author(s):  
Adam J George ◽  
Sarah L Bolt

Cattle are social animals, and an understanding of social associations and interactions is an important consideration when managing herds. Knowledge of this can facilitate positive welfare and productivity and it can also help to reduce the spread of disease. Social network analysis (SNA) is a tool that can be used to assess specific social interactions within cattle groups and help determine appropriate management actions in livestock enterprises. The aim of this review is to summarise how SNA can be used to study the social behaviour patterns of dairy cattle and highlight applications for this approach on dairy farms.

2019 ◽  
Vol 213 ◽  
pp. 47-54
Author(s):  
Inès de Freslon ◽  
Beatriz Martínez-López ◽  
Jaber Belkhiria ◽  
Ana Strappini ◽  
Gustavo Monti

Author(s):  
Joaquín Castillo de Mesa

El consenso científico señala que la mejor manera de frenar la propagación de la COVID-19 es mediante el rastreo de los contactos de las personas infectadas. Esta medida tiene carácter social, ya que busca analizar las redes de las personas para detectar de forma temprana quiénes están en riesgo de haber sido infectados, alertarles e imponerles la cuarentena, una medida de aislamiento social que impida la potencial propagación.  Hasta el momento mucho se ha hablado sobre qué profesionales deben realizar este rastreo pero poco acerca de cómo se debe realizar este rastreo. En este artículo, en primer lugar, se define qué es el rastreo, qué profesionales están más preparados para estas tareas y cómo se está llevando a cabo en España, encontrando ciertas carencias en cuanto al uso de metodologías científicas que apoyen la labor de rastreo. A partir de la literatura científica que analiza cómo afecta la socialización a la propagación se desarrolla una simulación sobre cómo se puede propagar la COVID 19 durante las interacciones sociales de las personas en sus distintos ámbitos de socialización. Sobre esta simulación se utiliza análisis de redes sociales y determinados algoritmos de detección de comunidades y de análisis de cohesión, para mostrar la idoneidad de estas metodologías para que el rastreo. Los resultados muestran que con el apoyo del análisis de redes sociales y de determinados algoritmos se accede de forma precoz a información clave sobre comunidades formadas en la estructura de red y sobre quiénes son los superpropagadores y los intermediadores entre las comunidades detectadas. Esto puede ayudar a priorizar la puesta en contacto con estas personas para cortar las cadenas de trasmisión comunitaria. Finalmente discutimos acerca de la idoneidad de que los profesionales del Trabajo Social se capaciten en estas metodologías para poder desarrollar esta labor del rastreo.Scientific consensus indicates that the best way to slow the spread of COVID 19 is by tracing the contacts of infected people. This measure has a social nature, since it seeks to analyze people’s networks to detect early who is at risk of being infected, alert them and impose quarantine, a measure of social isolation that prevents the potential spread. So far, much has been said about which professionals should perform this screening but Little about how it should be done. In this article, in the first place, it is defined what tracking is, which professionals are best prepared for the use of scientific methodologies that support tracking word. From the scientific literature that analyzes how socialization affects the spread, a simulation is developed on how COVID 19 can spread during the social interactions of people in their different areas of socialization. On this simulation, social network analysis and certain algorithms for community detection and cohesion analysis are used to show the suitability of these methodologies for tracking. The results show that with the support of social network analysis and certain algorithms, key information about communities formed in the network structure and who are the super-propagators and intermediaries between the detected communities is accessed early. This can help prioritize contacting these people to cut the chains of community transmission. Finally, we discuss the suitability for Social Work professionals to be trained in these methodologies in order to develop this tracking work.


Author(s):  
Jeffrey P. Copeland ◽  
Arild Landa ◽  
Kimberly Heinemeyer ◽  
Keith B. Aubry ◽  
Jiska van Dijk ◽  
...  

Social behaviour in solitary carnivores has long been an active area of investigation but for many species remains largely founded in conjecture compared to our understanding of sociality in group-living species. The social organization of the wolverine has, until now, received little attention beyond its portrayal as a typical mustelid social system. In this chapter the authors compile observations of social interactions from multiple wolverine field studies, which are integrated into an ecological framework. An ethological model for the wolverine is proposed that reveals an intricate social organization, which is driven by variable resource availability within extremely large territories and supports social behaviour that underpins offspring development.


Author(s):  
Sophie Mützel ◽  
Ronald Breiger

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.


Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teruyoshi Kobayashi ◽  
Mathieu Génois

AbstractDensification and sparsification of social networks are attributed to two fundamental mechanisms: a change in the population in the system, and/or a change in the chances that people in the system are connected. In theory, each of these mechanisms generates a distinctive type of densification scaling, but in reality both types are generally mixed. Here, we develop a Bayesian statistical method to identify the extent to which each of these mechanisms is at play at a given point in time, taking the mixed densification scaling as input. We apply the method to networks of face-to-face interactions of individuals and reveal that the main mechanism that causes densification and sparsification occasionally switches, the frequency of which depending on the social context. The proposed method uncovers an inherent regime-switching property of network dynamics, which will provide a new insight into the mechanics behind evolving social interactions.


2015 ◽  
Vol 6 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Iraj Mohammadfam ◽  
Susan Bastani ◽  
Mahbobeh Esaghi ◽  
Rostam Golmohamadi ◽  
Ali Saee

2009 ◽  
Vol 17 (3) ◽  
pp. 354-360 ◽  
Author(s):  
Maria Helena do Nascimento Souza ◽  
Ivis Emília de Oliveira Souza ◽  
Florence Romijn Tocantins

This study aimed to discuss the contribution of the social network methodological framework in nursing care delivered to women who breastfeed their children up to six months of age. This qualitative study aimed to elaborate the social network map of 20 women through tape-recorded interview. Social network analysis evidenced a "strong" bond between these women and members from their primary network, especially friends, neighbors, mothers or with the child's father, who were reported as the people most involved in the breastfeeding period. The contribution of this framework to nursing practice is discussed, especially in care and research processes. We believe that nurses' appropriation of this framework can be an important support for efficacious actions, as well as to favor a broader perspective on the social context people experience.


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