Evaluating Capacity Development in Planning, Monitoring, and Evaluation: A Case from Agricultural Research
Bibliographic record
Abstract
Capacity development has moved to center stage on the agendas of development organizations. As technologies and institutions are changing fast and budgets for overseas development assistance are declining, strengthening the capabilities of individuals, organizations, and institutions is essential to ensure that development efforts are sustainable and poverty is eradicated. Substantial sums are being invested in the development of organizational and institutional capacities. Yet, the design and management of capacity development efforts leaves much to be desired. Few capacity development programs have been systematically and thoroughly evaluated to test their underlying theories and assumptions, document their results, and draw lessons for improving future programs. This report describes the concepts and methods used to evaluate a regional capacity development project in Latin America. The project under study aims to strengthen planning, monitoring, and evaluation (PM&E) in agricultural research organizations in the region. The report outlines the procedures employed in five evaluation studies and summarizes the results of each study. It then presents consolidated findings in response to three evaluation questions: What were the main contributions of the project to agricultural research management? What lessons can be learned to improve the design of future capacity development programs? What lessons can be learned to improve future evaluations of capacity development?
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".