Chinese-russian cooperation in the automobile field : experience and prospects 2000-2022
Bibliographic record
Abstract
Cet article aborde la question de la présence des constructeurs automobiles chinois sur le marché russe. Sont analysés le positionnement et les difficultés que rencontrent les constructeurs chinois lors de leur entrée sur le marché russe. L’auteur examine le rôle des sanctions occidentales vis-à-vis de l’industrie automobile russe, notamment la manière dont les sanctions influencent la position des constructeurs chinois, sachant qu’officiellement, la Chine n’a jamais soutenu les sanctions contre la Russie. Enfin, l’auteur se concentre sur les changements causés par la guerre en Ukraine, qui a débuté en 2022. Cet événement a provoqué des changements tectoniques du marché automobile russe. Le départ des constructeurs occidentaux ouvre des perspectives importantes pour les constructeurs chinois dans le cas où les constructeurs occidentaux ne reviendraient pas sur le marché automobile russe dans un avenir proche.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".