Welt(en) verzeichnen / Recording Worlds
Bibliographic record
Abstract
Die Praxis des Verzeichnens spielt im naturkundlichen Sammeln eine zentrale, doch häufig übersehene Rolle. Listen, Etiketten und Inventarbücher sind Werkzeuge, mit denen Sammlungen und Wissen geordnet, Tiere klassifiziert und naturkundlichen Objekten Wert zugeschrieben wird. Sie beeinflussen maßgeblich die Art und Weise, wie wir die Welt begreifen, befinden sich aber auch selbst beständig im Wandel. 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". The practice of record-keeping plays a crucial, yet often overlooked role in natural history collecting. Lists, labels, and inventory books are tools to organise collections and knowledge, classify animals, and assign value to natural history objects. They significantly influence how we order and understand the (natural) world while continuously undergoing profound changes themselves. 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.008 | 0.010 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.014 | 0.014 |
| Research integrity | 0.008 | 0.022 |
| Insufficient payload (model declined to judge) | 0.105 | 0.131 |
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; both teacher heads agree on what is shown here.
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".