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New needs and training modalities for the sustainable transfer of know-how on food and agriculture statistics in the COVID-19 era

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This paper analyses the changing context and nature of training, with particular reference to the experience of FAO as a custodian agency for a large share of SDG indicators.

Topics

SDG
2030 Agenda
Breaking the silos
Leave no one behind
SDG2: Zero hunger
Subject
2030 Agenda and SDGs
Statistics
Demographic and social statistics
Living conditions, poverty and inequality
Methodology and statistical processes
Data dissemination and communication
Keywords
blended learning
capacity development
skills
training

The Sustainable Development Goals (SDGs) Global Indicator Framework (GIF) has multiplied training needs due to the large number of new indicators to be monitored by countries, whereas COVID-19-related social distancing restrictions have provided an unexpected springboard for the proliferation of cutting-edge virtual training tools and modalities. This has exposed a panoply of new data-related skills needed by contemporary statisticians, and therefore the types of training that could be most appropriate for acquiring these skills. This paper analyses the changing context and nature of training, with particular reference to the experience of FAO as a custodian agency for a large share of SDG indicators. The combination of different learning modalities, appropriately blended into a coherent learning programme, is shown to have the greatest impact, with one modality reinforcing the strengths and dampening the limitations of another.

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