COVID-19 Policy Response Monitor for German Federal States (CPRM-Ger): A Dataset on Non-pharmaceutical Interventions in Germany
Bibliographic record
Abstract
The COVID-19 Policy Response Monitor for German Federal States builds on the idea and methodology of the Oxford Covid-19 Government Response Tracker (OxCGRT) and is adapted to the specific conditions of the German federal system (see Codebook). The presented dataset contains a collection of 31 types of non-pharmaceutical interventions (NPIs) that were implemented in the 16 German federal states between March 12 and August 31, 2020. Depending on the level of strictness of the applied measures, an overall Stringency index as well as eight Sub-indices regarding Events and gatherings, Movement, Childcare and education, Business, Food and catering, Leisure facilities, Health sector, and Public hygiene have been calculated for each federal state. Sub-indices and items: E - Events and gatherings E1 - Indoor public event restriction E2 - Outdoor public event restriction E3 - Private gathering in public restriction E4 - Private gathering on private property restriction E5 - Religious gathering restriction E6 - Freedom of assembly restriction E7 - Private special event restriction M - Movement M1 - Stay at home orders M2 - Public transport closing M3 - Internal movement restriction M4 - International travel restriction M5 - Tourism restriction C - Childcare and education C1 - Kindergarten closing C2 - School closing C3 - University closing B - Business B1 - Shop closing B2 - Close-contact services closing F - Food and catering F1 - Restaurant closing F2 - Snack stand closing F3 - Bar closing L - Leisure facilities L1 - Playground closing L2 - Outdoor sports facility closing L3 - Indoor sports facility closing L4 - Leisure park and zoo closing L5 - Theatre, cinema and seated concert closing L6 - Museum and exhibition closing L7 - Music club and concert closing H - Health sector H1 - Health and nursing services restriction H2 - Hospital visitors restriction H3 - Nursing facility visitors restriction P - Public hygiene P1 - Person-to-person distance obligation P2 - Facemask obligation* (not included in Stringency Index to avoid double counting) The coding guidelines are availible in German only.
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.
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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".