'Fair trade gold': Antecedents, prospects and challenges

This paper critically examines the challenges with, and impacts of, adopting the models in place for fair trade agriculture in the artisanal gold mining sector. Over the past two years, an NGO-led 'fair trade gold' movement has surfaced, its crystallization fuelled by a burgeoning body of evidence that points to impoverished artisanal miners in developing countries receiving low payments for their gold, as well as working in hazardous and unsanitary conditions. Proponents of fair trade gold contest that increased interaction between artisanal miners and Western jewellers could facilitate the former receiving fairer prices for gold, accessing support services, and ultimately, improving their quality of life. In the case of sub-Saharan Africa, however, the gold being mined on an artisanal scale does not supply Western retailers as perhaps believed; it is rather an important source of foreign exchange, which host governments employ buyers to collect for their coffers. It is maintained here that if the underlying purpose of fair trade is to improve the livelihoods and well-being of subsistence producers in developing countries, then the models that have proved so successful in alleviating the hardships of agro-producers of 'tropical' commodities such as coffee, tea, bananas and cocoa, should be adapted to artisanal gold mining in sub-Saharan Africa. Campaigns promoting 'fair trade gold' in the region should view host governments, and not Western retailers, as the 'end consumer', and focus on improving governance at the grassroots, organizing informal operators into working cooperatives, and addressing complications with purchasing arrangements - all of which would go a long way toward improving the livelihoods of subsistence artisanal miners. A case study of Noyem, Ghana, the location of a sprawling illegal gold mining community, is presented, which magnifies these challenges further and provides perspective on how they can be overcome. (c) 2007 Elsevier Ltd. All rights reserved.

Categories of GM risk-benefit perceptions and their antecedents

The stated benefits and perceived risks of genetic modification (GM) cover very diverse issues, such as food safety, world food security, and the environment, that may differentially affect consumer acceptance. In this research, we hypothesize that consumers perceive up to eight dimensions: risks to business (farmers, agribusiness, etc.), benefits to business, risks and benefits to the environment, risks and benefits to the developing world, and risks and benefits to self and family. Moral concerns are also recognized. Using data collected in 2002 in the United States, France, and the UK, we investigate these different dimensions. Second, we analyze the extent to which the dimensions of risk-benefit perceptions can be explained by general attitudes widely used to explain food purchase behavior (such as general attitude to the environment, to technology, etc.), as well as by perceived knowledge of GM, level of education, and trust in various sources of information. In all locations, the majority of consumers only perceive a medium level of risk from GM products. Attitude to technology is the most important attitude variable—those with a positive attitude to technology in general also have a positive attitude to GM technology. More Americans than Europeans fall into this category. Those who trust government and the food industry tend to think GM technology is less risky, whereas those who trust activists believe the opposite. Americans are more trusting of the former, Europeans of the latter. Level of education is positively associated with benefit perceptions and negatively associated with moral concerns. Location continues to play a limited independent role in explaining perceptions even after these factors have been taken into account.

The automatic identification and prioritisation of criminal networks from police crime data

The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.