The role of social networks in inclusion of small-scale producers in agri-food developing clusters

This paper discusses how network theory and social capital can help explain different patterns of inclusion of small-scale and medium sized producers in agri-food clusters. We make the argument that despite the centralized nature of practices, the manner in which inclusion takes place can vary significantly depending on structural features of local networks and governance factors, especially social capital and the role of lead organisations. Social network analysis allows us to investigate how different patterns of bonding, bridging and centrality of key actors in agricultural clusters can influence diffusion of knowledge. We frame this discussion through a typology that allows us to identify diverse scenarios of inclusion of small-scale producers. This is then used to guide an empirical analysis of two agri-food clusters of small-scale producers in Peru (mango) and Colombia (palm oil). Judicious use of mixed methods and the typology can prove useful to explain diverse patterns of inclusion which have important implications for small-scale agricultural producers

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Distinguishing patterns of learning and inclusion through the dynamics of network formation in developing agricultural clusters

A significant development in the economies of a number of less developed Latin American countries over the past decade has been the mushrooming of export and commodity-based agricultural clusters in hitherto economically underdeveloped regions, many of which are dominated by small-scale agricultural production. A consequent challenge for policy makers is to develop strategies that offer small-scale local producers opportunities to upgrade into more specialised higher value-added activities (Schmitz & Nadvi 1999, Gibbons 2001). We discuss three types of networks based on different degrees of network cohesion and roles of strategic actors. Debates on how to create more efficient production for small-scale agricultural producers emphasize the social, as much as the technological features of small-scale production. Two key issues emerge. The first of these relates to local participation, civic engagement and social capital, which are seen as a precursor to achieving some degree of coordinated action by local actors (Mansuri and Rao 2013). This discussion extends beyond simple connectivity, to the recognition of the need to “embed” groups that instil social norms on their members and can hold people accountable (Tsai 2007). Secondly, there is a focus on the role strategic actors play in learning processes at local cluster level. Within the innovation literature, lead firms are the central unit for the implementation of new technologies, and it is assumed that, through a variety of mechanisms, good practices can be disseminated to other local actors. By contrast, within the development literature, the role of key firms has often been balanced through a discussion of the benevolent and malevolent effects of the capture of resources by local elites (Abraham and Platteau 2004, Rao and Ibanez 2005). The motivation for this paper is to understand the dynamics of local participation in processes of learning with different lead actors as opportunities for export and/or commodity production within clusters emerge. We conceptualize this dynamic using social network analysis (SNA), the analytical approach of which is grounded in social capital theory and is built around the twin concepts of network cohesion (the degree of mutual socialization) and the position that focal actors hold within a network (Burt, 1992; Gargiulo & Benassi, 2000). Hence, the structural features of the networks provide insights into the connectedness of actors, while the position of individual actors in the network provides measures of the diverse resources some strategic organisations have at their disposal through the connections they have access to (Carpenter et al. 2012). This allows us to make some predictions regarding how different patterns of connectivity, cohesion and centrality of key actors in the cluster can influence learning, diffusion of knowledge and the degree of dependence some organisations have over others in these emerging clusters. The empirical data was gathered firstly through two surveys of producer organisations in two “emerging” agricultural clusters, the Palm oil cluster in Colombia (22 organisations) and the mango cluster in Northern Peru, (26 organisations), both of which contain large numbers of small-sized producers and have experienced rapid growth in the recent period but demonstrate quite different network structures. From these two case studies, we extrapolate three types of network structures that have quite different patterns of inclusion, lead organisations and knowledge diffusion dynamics. Taking these three as separate case-types, a series of interviews were then undertaken with local producers, service organisations and policy makers to provide further depth to our analysis of these networks. The Figure 1 shows each of these variables on different measurement planes. The dominance of focal actors is measured by the degree centrality (Freeman 1979). For cohesion we look at the K-core measure of sub-clusters (Doreian and Woodard 1994). The degree of learning we look at the in-degree for knowledge from outside the cluster. We firstly identify a network with one highly dominant producer organisation surrounded by small-scale producers. In this case, network theory suggests that networks will be highly asymmetric, i.e. most vertices have a limited activity and a few vertices have a very strong ability to acquire external knowledge and develop network ties (Coward and Jonard 2009). In these circumstances, inequality will be high and can be locked-in, as a large firm will benefit directly from new opportunities and there exist vast differences in capabilities and weak resources of small producers. Here inclusion in learning is likely to occur primarily through a process of “meme transmission” i.e. imitation and a paternalist relation. Secondly, we identify a network with few lead producer organisations, and learning as well as diffusion of knowledge rely upon an ecosystem of service organisations coordinated by producer associations. In this case, high cohesion and the establishment of a cooperative infrastructure of endogenous institutions through which common pool resources and technology can be managed is critical. Networks based on cooperative infrastructures are more likely to use the network as a space to learn and provide new practices, rather than a simple information transmission mechanism. Finally, we distinguish a network that resembles Schumpeterian characteristics, where a number of firms both compete and cooperate and have access to external networks. In this case, the network is defined by the need for access to markets and commercial rather than cooperative prerogatives. The above distinctions emphasize that inclusive processes of learning requires an understanding of the nature of the local networks, that incorporate the role of local leaders, the nature of connectivity and the existence of cooperative institutions. These features will have important implications for guiding the intervention of policy makers

Limited evidence of physical therapy on balance after stroke: A systematic review and meta-analysis.

BackgroundStroke results in balance disorders and these directly affect autonomy and quality of life. The purpose of this systematic review and meta-analysis was to determine the efficacy of physical therapy (PT) on balance and postural control after stroke.MethodsWe included all randomized controlled trials assessing the efficacy of PT on balance and postural control in adult patients after stroke without language restriction. Medline, Embase/Scopus, Cochrane Central Register of Controlled Trials, PEDro, Pascal, and Francis databases were searched until January 2019. Primary outcomes were balance (Berg Balance scale and Postural Assessment Scale for Stroke) and postural control with postural deviation or stability measurement in sitting or standing static evaluation. A pair of independent reviewers selected studies, extracted data, and assessed risk of bias. Meta-analyses with subgroups (categories of PT, time post-stroke, and lesion location) and meta-regression (duration of PT) were conducted.ResultsA total of 145 studies (n = 5912) were selected from the 13,123 records identified. For balance, evidence was found in favor of the efficacy of functional task-training alone (standardized mean difference 0.39, 95% confidence interval [0.09; 0.68], heterogeneity I2 = 63%) or associated with musculoskeletal intervention and/or cardiopulmonary intervention (0.37, [0.19; 0.55], I2 = 48%), electrostimulation (0.91, [0.49; 1.34], I2 = 52%) immediately after intervention, compared to sham treatment or usual care (ST/UC). For postural deviation eyes open, assistive devices were more effective than no treatment (-0.21, [-0.37; -0.05], I2 = 0%) immediately after intervention; for postural stability eyes open, functional task-training and sensory interventions were more effective than ST/UC (0.97, [0.35; 1.59], I2 = 65% and 0.80, [0.46; 1.13], I2 = 37% respectively) immediately after intervention.ConclusionsFunctional task-training associated with musculoskeletal intervention and/or cardiopulmonary intervention and sensory interventions seem to be immediately effective in improving balance and postural stability, respectively. The heterogeneity of PT and the weak methodological quality of studies limited the interpretation and the confidence in findings