An In-Depth International Comparison of Major Donor Agencies: How Do They Systematically Conduct Country Program Evaluation?
Bibliographic record
Abstract
Background: This paper presents an in-depth international comparison of systems and procedures of aid evaluation, focusing on Country Program Evaluation among major donor agencies. The original client of this study is Ministry of Foreign Affairs, Japan (MOFAJ). Purpose: The purposes of this paper are set as follows: (1) to understand how aid agencies conduct Country Program Evaluation; and (2) to make recommendations for improvement of the current practice of Country Program Evaluation in the aid evaluation community. Setting: The examined donors include: the World Bank (WB), the Asian Development Bank (ADB), the Inter-American Development Bank (IADB), the United Nations Development Programme (UNDP), the U.S. (USAID), Canada (CIDA), the U.K. (DFID), the Netherlands (IOB), Germany (BMZ), France (Foreign Ministry), and Japan (Ministry of Foreign Affairs (MOFAJ)). In addition, aid agencies conducting respective project evaluation are also examined, and they are JICA (Japan), GTZ and KfW (Germany) and AFD (France). Intervention: This study presents the result of comparative analysis among those donor agencies in terms of the following viewpoints: (1) evaluation criteria employed; (2) approaches to evaluate “effectiveness” and “impact”; (3) attribution issue; (4) the use of a rating system; and (5) overall evaluative conclusion and integrating methods. All viewpoints are focusing on Country Program Evaluation. One conclusion is that most agencies have been struggling with how to judge the degree and value of their country programs. Data Collection and Analysis: Mixed methodologies were employed to collect data from the said donor agencies. The analysis was conducted by a systematic procedure consisting of: (i) summarizing information in a comparative table; (ii) trying to make groups/categories based on common characteristics if possible; and (iii) examining and concluding basic thoughts/philosophy which make their differences. Findings: This study made some new knowledge about how aid agencies conduct Country Program Evaluation and identified several issues remained. Varieties of their practices are observed and it is far from the unified methods agreed. Some remarkable points identified in this study are:(1) Most aid agencies invoke the DAC five evaluation criteria for Country Program Evaluation. (Major exception was USAID); (2) “Strategic relevance” and “coherence/complementarity” are the emerging new criteria; (3) Attribution is still the issue that aid agencies have struggled; and (4) The attitude for introduction of rating system is clearly divided among aid agencies.
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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 | 0.332 | 0.289 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".