1,727,833 research outputs found
How countries plan to address agricultural adaptation and mitigation: An analysis of Intended Nationally Determined Contributions. CCAFS dataset
Data presented here are the result of an analysis of the adaptation and mitigation contributions of the 162 INDCs (representing 189 Parties) submitted to the UNFCCC as of 28 April 2016, and then revised using information submitted through 31October 2016. Related Info Notes were written using the data as of 28 April 2016: http://hdl.handle.net/10568/69115 and http://hdl.handle.net/10568/68990
Related Info Notes: http://hdl.handle.net/10568/69115 and http://hdl.handle.net/10568/6899
Outcome-based innovation and scaling, impact with systems framework
How can we, and those who have been structurally excluded, become more robust AR4D actors? How can we educate ourselves to excel in interdisciplinary work and recognize biases within our project teams? What are the consequences of failing to address these systemic issues to our effectiveness?
Our new research portfolio delves into these questions, recognizing that this endeavor is not only a moral imperative but also crucial for enhancing our capabilities and success in the field. This research commentary series, explores five research themes shaping the future of A4RD with systems thinking, using qualitative and quantitative methods:
1. Investigating upstream agriculture research for development dynamics for downstream impacts
https://hdl.handle.net/10568/139930
2. Integrating social and natural sciences in agricultural innovation systems https://hdl.handle.net/10568/139931
3. Obstacles to measuring and quantifying systems change https://hdl.handle.net/10568/139932
4. Outcome-based innovation and scaling, impact with systems framework https://hdl.handle.net/10568/139936
5. Considering social differentiation in innovation and scaling https://hdl.handle.net/10568/13994
Integrating social and natural sciences in agricultural innovation systems
How can we, and those who have been structurally excluded, become more robust AR4D actors? How can we educate ourselves to excel in interdisciplinary work and recognize biases within our project teams? What are the consequences of failing to address these systemic issues to our effectiveness?
Our new research portfolio delves into these questions, recognizing that this endeavor is not only a moral imperative but also crucial for enhancing our capabilities and success in the field. This research commentary series, explores five research themes shaping the future of A4RD with systems thinking, using qualitative and quantitative methods:
1. Investigating upstream agriculture research for development dynamics for downstream impacts https://hdl.handle.net/10568/139930
2. Integrating social and natural sciences in agricultural innovation systems https://hdl.handle.net/10568/139931
3. Obstacles to measuring and quantifying systems change https://hdl.handle.net/10568/139932
4. Outcome-based innovation and scaling, impact with systems framework https://hdl.handle.net/10568/139936
5. Considering social differentiation in innovation and scaling https://hdl.handle.net/10568/13994
Community seed banks: Farmers’ handbook (updated version). Establishing a community seed bank: Booklet 1 of 3
Chinese version of How to develop and manage your own community seed bank: Farmers’ handbook (updated version). Establishing a community seed bank: Booklet 1 of 3. This handbook is a companion to Vernooy, R., Sthapit, B. and Bessette, G. (2020). Community seed banks: concept and practice. Facilitator handbook (updated version). Bioversity International, Rome, Italy (https://hdl.handle.net/10568/81286). The three booklets making up this handbook were written and designed for rural producers who are interested in establishing, supporting, and managing a community seed bank. Each booklet focuses on a theme presented by the members of a community seed bank in Africa, Asia, and Latin America. Booklet 2 of 3 (Chinese) can be found here: https://hdl.handle.net/10568/113974. Booklet 3 of 3 (Chinese) can be found here: https://hdl.handle.net/10568/113975. Translation and adaptation to the local language is encouraged. If you would like to receive a hard copy of the booklets or give feedback or suggestions for improvement, please contact [email protected]
Investigating upstream agriculture research for development dynamics for downstream impacts
How can we, and those who have been structurally excluded, become more robust AR4D actors? How can we educate ourselves to excel in interdisciplinary work and recognize biases within our project teams? What are the consequences of failing to address these systemic issues to our effectiveness?
Our new research portfolio delves into these questions, recognizing that this endeavor is not only a moral imperative but also crucial for enhancing our capabilities and success in the field. This research commentary series, explores five research themes shaping the future of A4RD with systems thinking, using qualitative and quantitative methods:
1. Investigating upstream agriculture research for development dynamics for downstream impacts
https://hdl.handle.net/10568/139930
2. Integrating social and natural sciences in agricultural innovation systems https://hdl.handle.net/10568/139931
3. Obstacles to measuring and quantifying systems change https://hdl.handle.net/10568/139932
4. Outcome-based innovation and scaling, impact with systems framework https://hdl.handle.net/10568/139936
5. Considering social differentiation in innovation and scaling https://hdl.handle.net/10568/13994
Improving dairy cattle productivity in Senegal
ILRI Policy Brief 22, see https://cgspace.cgiar.org/handle/10568/8899
Obstacles to measuring and quantifying systems change
How can we, and those who have been structurally excluded, become more robust AR4D actors? How can we educate ourselves to excel in interdisciplinary work and recognize biases within our project teams? What are the consequences of failing to address these systemic issues to our effectiveness?
Our new research portfolio delves into these questions, recognizing that this endeavor is not only a moral imperative but also crucial for enhancing our capabilities and success in the field. This research commentary series, explores five research themes shaping the future of A4RD with systems thinking, using qualitative and quantitative methods:
1. Investigating upstream agriculture research for development dynamics for downstream impacts
https://hdl.handle.net/10568/139930
2. Integrating social and natural sciences in agricultural innovation systems https://hdl.handle.net/10568/139931
3. Obstacles to measuring and quantifying systems change https://hdl.handle.net/10568/139932
4. Outcome-based innovation and scaling, impact with systems framework https://hdl.handle.net/10568/139936
5. Considering social differentiation in innovation and scaling https://hdl.handle.net/10568/13994
Considering social differentiation in innovation and scaling
How can we, and those who have been structurally excluded, become more robust AR4D actors? How can we educate ourselves to excel in interdisciplinary work and recognize biases within our project teams? What are the consequences of failing to address these systemic issues to our effectiveness?
Our new research portfolio delves into these questions, recognizing that this endeavor is not only a moral imperative but also crucial for enhancing our capabilities and success in the field. This research commentary series, explores five research themes shaping the future of A4RD with systems thinking, using qualitative and quantitative methods:
1. Investigating upstream agriculture research for development dynamics for downstream impacts
https://hdl.handle.net/10568/139930
2. Integrating social and natural sciences in agricultural innovation systems https://hdl.handle.net/10568/139931
3. Obstacles to measuring and quantifying systems change https://hdl.handle.net/10568/139932
4. Outcome-based innovation and scaling, impact with systems framework https://hdl.handle.net/10568/139936
5. Considering social differentiation in innovation and scaling https://hdl.handle.net/10568/13994
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