Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks

Bearman, Peter Shawn; Moody, James; Stovel, Katherine

doi:10.1086/386272

Cited by 634 publications

(473 citation statements)

References 40 publications

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“…A similar effect of social network externalities on health was found in studies evaluating smoking [16], food choices [36], alcohol consumption [25,35] sexually transmitted diseases [5,8,23,40] In these cases, the social determinants of lifestyles and habits, pre-existing social norms and social influence pressures explain the diffusion of unhealthy behaviours and the related diseases.…”

Section: The Network Medicine Approach To Public Health Policysupporting

confidence: 58%

Towards a Complexity-Friendly Policy: Breaking the Vicious Circle of Equilibrium Thinking in Economics and Public Policy

Squazzoni

2017

Understanding Complex Systems

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This chapter aims to discuss certain limitations of the dominant equilibrium thinking in policy and explore more complexity-friendly alternatives. If societies and markets are viewed as complex, non-equilibrium systems, understanding nonlinear, adaptive and evolving patterns emerging from agent behaviour in network structures is fundamental for policy purposes. This requires improved realism of the behavioural and social foundations on which policies are based. We must also reconsider the mantra of incentivisation, institutional design and the top-down regulation that typically dominates conventional policy. Recent cases of financial market regulation and health policies can help us to understand the importance of looking at the subtle ways in which people or organisations behave when exposed to social influence, and pre-existing social norms and network externalities. Changing the current policy narrative and exploring complexity-friendly concepts, instruments and methods requires a shift of focus of policy-making from forecast and prediction of system equilibrium in order to understand and manage complex social systems better.

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Section: The Network Medicine Approach To Public Health Policysupporting

confidence: 58%

Towards a Complexity-Friendly Policy: Breaking the Vicious Circle of Equilibrium Thinking in Economics and Public Policy

Squazzoni

2017

Understanding Complex Systems

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“…We urge our (predominately middleclass, white and heterosexual) students to reflect on their sexual histories and connections to local/global networks of known and unknown others. Situated as they are in an internationally diverse community that revels in its title as 'Britain's top match-making university', and which enjoys a vigorous social scene, we suggest that like other young people, their sexual networks are probably complex (see Berman et al, 2004;Vivancos et al, 2008), and sexualhealth risk more proximate than they assume. We remain surprised, therefore, when mobile blood collection units visiting campus fail to encourage any real reflection on actual practice.…”

Section: Unpacking Heterosexualitymentioning

confidence: 90%

Blood, sex and trust: The limits of the population-based risk management paradigm

Kesby

Sothern

2014

Health & Place

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1 Blood, sex and trust: the limits of the population-based risk management paradigm.Keywords: Blood donation; HIV; risk-group; trust; MSM AbstractBlood screening is imperfect so Donor Health Check questionnaires (DHC) are used to defer those whose 'behaviour' suggests disproportionate risk of Blood Borne Infection (BBI).Taking the UK case, we compare deferment of three sub-populations with different HIV prevalence; Men-who-have-Sex-with-Men (4.7%), black-Africans (3.7%) and 'the-general-(heterosexual)-population' (c.0.09%) arguing that, with respect to STIs, DHCs assess risk based on broad population-level risk-groups not behaviour. This approach relies on an imaginative geography that distances heterosexual risk from the domestic population. Most DHCs knowingly commit the ecological fallacy allowing population-level statistics to obscure within-group diversity, identifying inadequately the risk posed by 'low-risk-groups'. The disjuncture between ontological risk phenomenon (diverse sexual practice) and the epistemological grid used to map risk (homogenized risk-groups) needs examination.Unpacking the category 'heterosexual' would both better differentiate risk within this group and change the relative-risk calculated for 'high-risk groups'. We call for practice-based DHCs that more accurately assess all potential donors.

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“…One work using reachability graphs is Bearman et al [14] that studies dating between high-school students. Their data fits the interval-graph framework (Fig.…”

Section: A Reachability Graphsmentioning

confidence: 99%

Temporal networks

2012

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A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names

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Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks

Cited by 634 publications

References 40 publications

Towards a Complexity-Friendly Policy: Breaking the Vicious Circle of Equilibrium Thinking in Economics and Public Policy

Towards a Complexity-Friendly Policy: Breaking the Vicious Circle of Equilibrium Thinking in Economics and Public Policy

Blood, sex and trust: The limits of the population-based risk management paradigm

Temporal networks

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