Organizational learning capacity and international development project success in West Africa: A case study
Bibliographic record
Abstract
Very few studies have focused on organizational learning within a team as a key success factor for international development projects. In particular, the relationship between organizational learning capacity, organizational efficacy, and project success has received little attention. This is the objective of this case study. It explores this relationship based on 23 semi-structured interviews with project coordinators, team members, and beneficiaries of two projects financed by the West African Development Bank (WADB) in Benin and Senegal. The results show that the social process of developing organizational learning capacity within a project team is a crucial issue for organizational efficacy and project success. Points for practitioners Within a team, establishing a framework for developing organizational learning capacity, characterized by autonomy, experimentation, and interaction with stakeholders, is a key project success factor. Flexible and adaptive approaches may foster organizational learning and help explore, through action, new project capacities. Such approaches may help increase the odds of project success in terms of international development and, thus, create value for stakeholders including beneficiaries.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".