<scp>UNESCO</scp>, the Faure Report, the Delors Report, and the Political Utopia of Lifelong Learning
Bibliographic record
Abstract
Two education reports commissioned by the United Nations Educational, Scientific and Cultural Organization ( UNESCO ), Learning to be , otherwise known as the F aure report (1972) and Learning: The treasure within , otherwise known as the D elors report (1996), have been associated with the establishment of lifelong learning as a global educational paradigm. In this article, which draws on archival research and interviews, I will explore how these two reports have contributed to debates on the purpose of education and learning. In the first half, I will shed light on their origins, the context in which they came about, how they have been received by the education community and by UNESCO member states and how they have been discussed in the scholarly literature. In the second half, I will discuss the key themes of the reports, in particular lifelong learning as the global educational ‘master concept’. In the last section, I will reflect on how the F aure report and the D elors report are still relevant for our debates about learning today. I will argue that the concept of lifelong learning, as put forward by these reports, was a political utopia which is at odds with today's utilitarian view of education.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".