Does Research Reduce Poverty? Assessing the Welfare Impacts of Policy‐oriented Research in Agriculture
Bibliographic record
Abstract
In the current context of the global financial crisis and its aftermath, development resources are likely to be getting scarcer. Resources for development research are too. The set of circumstances generating the resource scarcity is also putting pressure on development gains. More than ever before, every dollar spent on development research will have to count towards sustainable poverty reduction. However, the understanding of the impacts of development research on policy change and on poverty is weak at best, with agriculture being no different. The area of research impact is not a new area of enquiry but an emergent one. Our paper seeks to build on the work of others. It surveys the literature and identifies different ways of assessing the impact of ‘policy-oriented’ research. We then take the available literature on agriculture as a specific focus to survey. Our paper surveys the different types of ‘policy-oriented’ research; the literature on the ‘theories of change’ for policy research in international development; methodologies for analysing the impact of policy-oriented research; the relevant agriculture literature and outlines the types indicators that can be used for impact assessment of research with examples. The key findings are: • There is no standard practice for the evaluation of research projects and every evaluation strategy should be designed on a case-by-case basis. • It is possible to test research project impacts along some dimensions of social welfare (agricultural output, income or poverty) by finding the appropriate indicators (and methodology). The overall goal – welfare impacts of research – is highly desirable, but not always feasible. • When welfare assessment of research is not feasible, it is recommended that evaluators test intermediate outcomes. The articulation of the theory of change of the project allows testing critical links in the causal chain running from research to welfare.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.248 | 0.411 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".