The High Frequency Firm Survey “Bundesbank Online Panel – Firms”
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
Abstract The Bundesbank Online Panel – Firms (“BOP-F”) is a dataset with responses from a high frequency firm-level survey of the same name. The Bundesbank has conducted the survey since June 2020, and since July 2021 the survey has been carried out at a monthly frequency. Every month, around 3000 firms from all economic sectors, regions and size classes are surveyed. The survey consists of recurring core questions about the economic situation of firms and their expectations and special questions that usually differ from quarter to quarter. The latter often relate to current topics, for instance, climate change, digitalization, Covid-19. The data can be accessed for research and especially the possibility to combine it with other administrative Bundesbank data makes it particularly valuable for research. The objective of this paper is to describe the methodology of the data collection, the content data as well as the data’s research potential.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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