Dubieuze verwervingen en het Advies over de omgang met koloniale collecties
Bibliographic record
Abstract
A new Dutch approach to dealing with collections from colonial contexts Several countries in Europe are developing new policies for dealing with collections from colonial contexts. In October 2020, the Council for Culture also made a contribution to this matter commisioned by Minister Van Engelshoven with the Advice for dealing with colonial collections. This article makes two caveats to this advice. The first is about provenance research, about which the advisers have a lot to say, but clues are lacking as to how museums can balance this kind of time-consuming and costly research with the large number of dubiously acquired objects from colonial contexts awaiting investigation. Second, the author misses references to how claims for two other categories of looted art involving Europeans are handled: those of human remains and objects from the early inhabitants of European settler colonies (Australia, Canada, New Zealand, USA and South Africa) and Nazi-looted art. Those early inhabitants and the descendants of the victims of the Nazi regime have made more progress with their restitution requests than the old colonies with theirs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".