Zoos und Artenschutz / Zoos and Conservation
Bibliographic record
Abstract
Zoos bewerben sich heute als Artenschutzzentren. Bis in die 1970er Jahre wurde die Mehrzahl der ausgestellten Tiere allerdings in der Wildnis gefangen. Welche Entwicklungen haben Zoos durchlaufen und welche Dilemmata haben sich ergeben? Tiere als Objekte? ist eine Online-Publikation von Wissenschaftler:innen des Museums für Naturkunde Berlin, des Berliner Zoos und der Humboldt-Universität zu Berlin, herausgegeben von Ina Heumann und Tahani Nadim. Die Publikation ist Teil des vom BMBF-geförderten Forschungsprojekts "Tiere als Objekte. Zoologische Gärten und Naturkundemuseum in Berlin, 1810 bis 2020". In recent times, zoos have begun advertising themselves as centres for species conservation. Well into the 1970s, however, a majority of their animals had been caught in the wild. What changed zoos and what dilemmas are they facing? Animals as Objects? is an online publication by researchers from the Museum für Naturkunde Berlin, the Zoo Berlin, and the Humboldt-Universität zu Berlin, edited by Ina Heumann and Tahani Nadim. It was funded by the BMBF as part of the research project "Animals as Objects. Zoological Gardens and Natural History Museum in Berlin, 1810 to 2020".
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.089 | 0.010 |
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".