Bibliographic record
Abstract
In September 2010, Moscow hosted the International Arctic Forum “The Arctic—Territory of Dialogue.” The Arctic Forum focused its attention on elements of sustainable development in the Arctic region, i.e., ecology, economics, infrastructure, social services, security, and geopolitics. Many Russian experts and many well-known politicians and experts from leading research centers of the Arctic countries (Canada, Denmark, Finland, Iceland, Norway, Sweden, and USA), as well as by participants from France, Germany, Netherlands, and other countries attended the forum. Scholars and public figures from the European countries, representatives of the NATO, the Organization for Security and Cooperation in Europe and other institutions were also present at the conference. In his key-note speech the Chairman of the Board of Trustees of the Russian Geographical Society (RGS), Prime Minister of the Russian Federation, Vladimir V. Putin formulated the principles of Russian national policy in the Arctic. Russian and foreign participants supported the idea of continuing dialogue on the Arctic under the RGS’s aegis and the transformation of the Arctic Forum into a permanent platform for discussions on the most urgent issues of the region.
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 | 0.016 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".