The recent literature on "complex contagions" challenges Granovetter's classic hypothesis on the strength of weak ties and argues that, when the actors' choice requires reinforcement from several sources, it is the structure of strong ties that really matters to sustain rapid and wide diffusion. The paper contributes to this debate by reporting on a small-N study that relies on a unique combination of ethnographic data, social network analysis, and computational models. In particular, we investigate two rural populations of Indian and Kenyan potters who have to decide whether adopting new, objectively more efficient and economically more attractive, technical/stylistic options. Qualitative field data show that religious sub-communities within the Indian and Kenyan populations exhibit markedly different diffusion rates and speed over the last thirty years. To account for these differences, we first analyze empirically observed kinship networks and advice networks, and, then, we recreate the actual aggregate diffusion curves through a series of empirically-calibrated agent-based simulations. Combining the two methods, we show that, while single exposure through heterophilious weak ties were sufficient to initiate the diffusion process, large bridges made of strong ties can in fact lead to faster or slower diffusion depending on the type of signals circulating in the network. We conclude that, even in presence of "complex contagions", dense local ties cannot be regarded as a sufficient condition for faster diffusion.
The region of Southern Ethiopia (Borana) and Northern Kenya (Marsabit) is characterised by erratic rainfall, limited surface water, aridity, and frequent droughts. An important adaptive response to these conditions, of uncertain antiquity, has been the hand-excavation of a sequence of deep wells at key locations often along seasonal riverbeds and valley bottoms where subterranean aquifers can be tapped. Sophisticated indigenous water management systems have developed to ensure equitable access to these critical water resources, and these are part of well-defined customary institutional leadership structures that govern the community giving rise to a distinctive form of biocultural heritage. These systems, and the wells themselves, are increasingly under threat, however, from climate change, demographic growth, and socio-economic development. To contribute to an assessment of the scale, distribution and intensity of these threats, this study aimed to evaluate the land-use land-cover (LULC) and precipitation changes in this semi-arid to arid landscape and their association with, and impact on, the preservation of traditional wells. Multitemporal Landsat 5, 7 and 8 satellite imagery covering the period 1990 to 2020, analysed at a temporal resolution of 10 years, was classified using supervised classification via the Random Forest machine learning method to extract the following classes: bare land, grassland, shrub land, open forest, closed forest, croplands, settlement and waterbodies. Change detection was then applied to identify and quantify changes through time and landscape degradation indices were generated using the Shannon Diversity Index fragmentation index within a 15 km buffer of each well cluster. The results indicated that land cover change was mostly driven by increasing anthropogenic changes with resultant reduction in natural land cover classes. Furthermore, increased fragmentation has occurred within most of the selected buffer distances of the well clusters. The main drivers of change that have directly or indirectly impacted land degradation and the preservation of indigenous water management systems were identified through an analysis of land cover changes in the last 30 years, supporting insights from previous focused group discussions with communities in Kenya and Ethiopia. Our approach showed that remote sensing methods can be used for the spatially explicit mapping of landscape structure around the wells, and ultimately towards assessment of the preservation status of the indigenous wells.
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The inception of agriculture in eastern Africa is a major topic of discussion among Africanist archaeologists, although very sparse evidence exists. Questions range from whether domestication was a local invention or whether it was introduced from the Near East, Asia, or elsewhere outside of Africa. These questions have remained unanswered because wild progenitors and models of the spread of African domesticates are yet to be established using undisputable data. The paucity of direct data has therefore necessitated the use of objects of material culture such as pottery, beads, burial cairns, architectural structures, and so on as indicators of pastoralism and cereal farming. In addition to the origins of African domesticates, research in eastern Africa has concerned itself with questions of farming technologies from later archaeological and historical times to the present. The remains of elaborate farming systems with extensive irrigation networks have drawn considerable attention. Though not unchanged, some of these farming systems remain in contemporary use in Kenya, Tanzania, and Ethiopia.
The Late Iron Age period in Kenya spans between 1000 BP and 200 BP. However, not much is known regarding this time period owing to the past direction of research in Kenya. Investigations concentrated on earlier archaeological periods due to the country’s richness in early human and technological evolution. As such the bias was not only in the research periods at the time but also, in the fact that, only those areas that were believed to yield such materials were explored. Most research was therefore conducted around the Kenyan Rift Valley until the late 1960s onwards, when the British Institute in Eastern Africa and others started to explore later archaeological and historical periods in the whole of Kenya. These researches, however, failed to recognize the evidence of mosaic in Iron Age sites, which was caused by complexities of diverse processes of replacement, admixture, interactions, and resistance in encounters between expanding and existing populations. Thus the name “Iron Age” for the period in question has been maintained denoting a period when iron was the most important or unique phenomenon, in total disregard of all the other social, political, and economic aspects. Use of oral traditions and genetic materials have, however, contributed greatly in filling the gaps, thus making it possible for archaeologists to understand the mosaic nature of archaeological materials resulting from interactions between populations who may have been culturally and socially distinct but lived during the same archaeological period. The available data show that the sites of this period range from open habitations, caves, and rock shelters to drystone structures, and that the human and environmental interactions were mutually beneficial to both. However, deeper understanding of land use and crop utilization is limited due to inadequate botanical datasets, since archaeobotanical recovery methods were rarely employed as a necessary direction of inquiry. This notwithstanding, as opposed to the environmental determinism theory, the populations of this period were not in sync with the environment, but rather, they were active participants who shaped it to suit their needs. Where resources such as water were not readily available, they improvised by tapping and managing them to suit their preferred occupations. Humans took advantage of natural landforms, climatic zones, and vegetation to shape different aspects of their lifestyles including economic subsistence, habitations, trade, and human-to-human interactions especially during environmental stress. Thus these populations must not be seen as helpless receivers from the environment, but active shapers and innovators of their lifestyles.
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