Growing demand for electric cars – German exports are also picking up
Bibliographic record
Abstract
Demand for electric vehicles is growing, both in Germany and around the world. Electric vehicles are also becoming more important for the German export market. In the first quarter of 2025, more than one in four cars exported from Germany was a battery-electric vehicle (BEV). On average, 82,000 BEVs worth EUR 3.4 billion were exported each month. Germany now generates a higher export surplus with BEVs than with other cars. The value of exports of BEVs exceeds the value of imports by a factor of 5. Besides, electric vehicles offer increasingly greater climate benefits. According to the KfW Energy Transition Barometer, one third of the electricity used to charge EVs in Germany is now self-generated and green, a new record. Consumer concerns about electric vehicles are decreasing. Approaches to increase EV uptake include removing information deficits, providing incentives for time-optimised charging and improving the conditions for charging in multi-family homes.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".