Heritage and interculturality in EU science diplomacy
Bibliographic record
Abstract
Abstract In recent years, culture and heritage have explicitly entered into science diplomacy debates and initiatives within the EU system and in EU’s foreign policy. For EU’s external relations heritage offers opportunities for developing partnerships based on shared, entangled histories but also challenges posed by dealing with difficult pasts of domination and colonialism. The paper, therefore, presents a new conceptual model for European science diplomacy that can enable more equitable ways of dealing with colonial heritage in relations between EU countries and partners outside Europe. It does so by combining recent literature on science diplomacy, heritage diplomacy, decolonial thinking, and on the concepts of interculturality. We argue that to engage successfully with colonial legacies and heritage, the concept of science diplomacy needs to be developed from a traditional “diffusionist” understanding towards a dialogical approach, which is epismologically open and acknowledges the inequalities in global knowledge production. In the second part of the paper, the practical implications of the theoretical framework are fleshed out in a discussion of three cases involving colonial heritage: The Tendaguru Fossil Collection, the Royal Museum for Central Africa in Brussels, and the work of Canadian indigenous artist Sonny Assu.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.043 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".