Researching the culture in agri-culture: social research for international development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dedication: Tribute to Robert King Merton, as a Founder of the Sociology of Science Foreword, Emil Q Javier and Per Pinstrup-Andersen Acknowledgements Contributors List of Abbreviations PART 1: SOCIAL RESEARCH FOR AGRICULTURAL POLICIES Concept and Method: The Uphill Route for Social Research in a Technological Environment, M M Cernea Agricultural Institutions and Receptivity to Social Research: The Case of the CGIAR, A H Kassam Who Are the Social Researchers of the CGIAR System? E Rathgeber, University of Ottawa, Canada PART 2: THE INSIDERS' VIEWS: SOCIAL RESEARCH IN THE CGIAR SYSTEM Rice for the Poor: The Call and Opportunity for Social Research, T R Paris, DAPO, Phillippines, S Morin, F G Palis, and M Hossain Understanding Forests-People Links: The Voice of Social Scientists, C J Pierce Colfer, CIFOR, Indonesia with E Dounias, M Goloubinoff, C Lopez, and W Sunderlin Humanizing Technology Development in the Green Revolution's Home, M R Bellon, CIMMYT, Mexico, M Morris, J Ekboir, E Meng, H De Groote, and G Sain Water to Thirsty Fields: How Social Research Can Contribute, M Samad, International Water Management Institute, Sri Lanka and D J Merrey Rootcrops in Agricultural Societies: What Social Research has Revealed, G Prain, CGIAR System-wide initiative on Urban & Peri-urban Agriculture, Lima, Peru, G Thiele, O Ortiz, and D Campilan Why the 'Livestock Revolution' Requires Research on People, D Romney, ILRI, Nairobi, Kenya and B Minjauw Aquatic Resources: Collective Resources and Severance for the World's Fish Wealth, K Kuperan Viswanathan, World Fish Center, Dhaka, Bangladesh, M Ahmed, P Thompson, P Sultana, M Dey, and M Torell Tropical Agriculture and Social Research: An Analytical Perspective, D Holland, Greening Australia, Inc, Australia, J Ashby, M Mejia, and J Voss. Dry Areas and the Changing Demands for Social Research, A A Aw-Hassan, International Center for Agricultural Research in the Dry Areas (ICARDA), Syria and M Abdelali-Martini Agricultural Biodiversity-and How Human Culture is Shaping It, P Eyzaguirre, IPGRI, Italy Studying Property Rights and Collective Action: A System-Wide Program, R Meinzen-Dick, CGIAR, USA Crafting Food Policy with Social Science Knowledge, R Meinzen-Dick, M Adato, M Cohen, C Farrar, L Haddad, and A Quisumbing PART 3: THE OUTSIDERS' VIEW: ISSUES, EXPECTATIONS, AND AGENDAS Not Just One Best System: The Diversity of Institutions for Coping with the Commons, E Ostrom, Indiana University, USA Social Research and Researchers in the CGIAR: Perceiving an Underused Potential, R Chambers, University of Sussex, UK The Rockefeller Foundation and Social Research in Agriculture, G Conway, The Rockefeller Foundation, USA, A Adesina, J Lynam, and J Moock A Donor Perspective on the Accomplishments, Limitations, and Opportunities for Social Research, S Bode, USAID/EGAT/ESP/IRB, USA and D Rubin Seeking Half our Brains: Constraints and Incentives in the Social Context of Interdisciplinary Research, R E Rhoades, University of Georgia, USA Roots: Reflections of a 'Rocky Doc' on Social Science in CGIAR, S Guggenheim, The World Bank, USA Social Science Knowledge as Public Good for Agriculture, D G Dalrymple, US Agency for International Development, USA Index.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it