Knowledge banking in global education policy: A bibliometric analysis of World Bank publications on public-private partnerships
Bibliographic record
Abstract
As a leading mobilizer of international development and educational knowledge, the World Bank has been critiqued in two key areas: (1) the dominance of economic thinking in its policies, and (2) its Northern-generated knowledge which informs its work in the Global South. In this paper, we investigate the disciplinary foundation of Bank knowledge, as well as its geographic representation. This study pays particular attention to knowledge mobilization relating to one of the most contentious policy prescriptions worldwide, and one that the Bank has historically supported: private sector engagement in education. By employing the concepts of economic imperialism and policy networks to frame our study, and through the use of a bibliometric methodological approach, we trace the authorship patterns of publications cited in a series of key World Bank documents on private sector engagement in education. Our findings show that the World Bank mobilizes research production from the Global North, which reflects a disproportionate economic disciplinary focus. Moreover, through a mapping of the cited authors, this network is shown to be highly narrow and privileges authors from a small subset of elite institutions.
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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 | 0.010 | 0.086 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.146 | 0.280 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".