Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the last few years there has been a tremendous surge in research projects focusing on the history of emotions. Historians all over the world, from Australia to London, from Princeton to Madrid, from Canada to Paris, have started to examine emotions from a historical perspective. Among the many individual and collective projects, the Berlin Center for the History of Emotions holds a special place. Since its founding in 2008, a group of twenty to thirty historians have devoted their research efforts to the single but complex goal of historicizing emotions. As an integral part of the Max Planck Institute for Human Development, the center is sufficiently funded to carry out such basic research and will continue to do so for years. It offers superb working conditions, providing offices and excellent library resources to its pre- and postdoctoral fellows and organizing weekly seminars and a great number of international conferences with the participation of distinguished scholars. Furthermore, the center welcomes visiting researchers (who mostly bring their own funding) and invites them to actively participate in and contribute to ongoing debates and events. Together with three major Berlin universities (Free University, Humboldt University, Technical University), the center launched an International Max Planck Research School for graduate training. Every year, six graduate students are accepted to the program, which focuses on moral economies of modern societies, with an emphasis on moral emotions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it