AidData has developed a set of open source data collection methods to track project-level data on suppliers of official finance who do not participate in global reporting systems. This codebook outlines the version 1.1 set of TUFF procedures that have been developed, tested, refined, and implemented... by AidData researchers and affiliated faculty at the College of William & Mary and Brigham Young University.
In the first iteration of this codebook, AidData's Media-Based Data Collection Methodology, Version 1.0, we referred to our data collection procedures as a “media-based data collection” (MBDC) methodology. The term “media-based” was misleading, as the methodology does not rely exclusively on media reports; rather, media reports are used only as a departure point, and are supplemented with case studies undertaken by scholars and non-governmental organizations, project inventories supplied through Chinese embassy websites, and grants and loan data published by recipient governments. In the interest of providing greater clarity, we now refer to our methodology for systematically gathering open source development finance information as the Tracking Underreported Financial Flows (TUFF) methodology. This codebook outlines the set of TUFF procedures that have been developed, tested, refined, and implemented by AidData staff and affiliated faculty at the College of William & Mary and Brigham Young University.
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This codebook outlines the set of TUFF procedures that have been developed, tested, refined, and implemented by AidData staff and affiliated faculty at the College of William & Mary. We initially employed these methods to achieve a specific objective: documenting the known universe of officially fin...anced Chinese projects in Africa (Strange et al. 2013, 2017). We have since then employed these methods to track Chinese official finance to five major world regions: Africa, the Middle East, Asia and the Pacific, Latin America and the Caribbean, and Central and Eastern Europe (Dreher et al. 2017). Additionally, other social scientists have adapted and applied the TUFF methodology to identify grants and loans from Gulf Cooperation Council (GCC) members (Minor et al. 2014), under-reported humanitarian assistance flows from traditional and non-traditional sources (Ghose 2017), foreign direct investment from Western and non-Western sources (Bunte et al. 2017), and pre-2000 foreign aid flows from China (Morgan and Zheng 2017). However, this codebook focuses specifically on TUFF data collection and quality assurance procedures to track Chinese official finance between 2000 and 2014.
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Through technical consultations with countries and partners, WHO has led the development of Preparedness and Resilience for Emerging Threats Module 1: Planning for respiratory pathogen pandemics. Version 1.0. The Module, currently available as an advanced draft, builds on previous pandemic lessons a...nd guidance, and has the following new elements:
It presents an integrated and efficient respiratory pathogen pandemic planning approach covering both novel pathogens and those known to have pandemic potential;
It enables coherence in addressing pathogen-agnostic and pathogen-specific elements for better preparedness;
It gives an organizing framework including operational stages and triggers for escalation and de-escalation between pandemic preparedness and response periods;
It contextualizes 12 IHR (2005) core capacities within the five components of health emergency preparedness, response and resilience (HEPR), from the respiratory threats perspective; and
It describes the critical sectors for respiratory pathogen pandemic preparedness to trigger multisectoral collaboration.
WHO will finalize and publish this Module after a global technical meeting that will be held on 24-26 April 2023.
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