International Education and Development: Histories, Parallels, Crossroads
Bibliographic record
Abstract
Education has been a priority sector when considering foreign aid allocationsince the 1970s. The stated objective has been to ensure universal access to basic education, with a more recent emphasis on quality and outcomes. Aware that these goals will not be met universally, the major actors involved in the post-2015 debate are turning back to the concept of learning. In this chapter, we briefly review major scholarly work and strategic papers that have shaped the discourse and policies of international development organisations and national actors over the past four decades. We discuss how the central notions of skills, learning, and both formal and non-formal education have evolved in conjunction with ideological shifts. We examine the tensions between public and private education as well as between individualised and standardised delivery modes. We further look at (big) data and online education promises. To conclude, we question the current focus of major stakeholders on post-2015, post-EFA agendas. As several articles in this special issue underscore, national policies and local practices are largely driven by persistent political economy dynamics while the influence of ‘the global agenda’ tends to remain confined to the international cooperation community itself.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".