Green Economy through the Rosia Montana Case - Best Solution in the Context of Schemes Offshore Routed by the International Corporations
Bibliographic record
Abstract
The object of researching paper, prepared by the student Nicolae Moroianu, under by Anişoara POPA, doc. conf. at University of Galati Lower Danube in analysis of the controversial case ” Roşia Montană - gold exploitation”. The utility of estimating needs for a structured analysis of the Roşia Montană case it is actually in Romanian society. Acording with the last 15 years, many conflicting tensions occurred between citizens, corporate officials, journalists, civil society actors and Presidential, Government and Parliament representatives. In this period, all stakeholders have provided often conflicting information and opinions on the benefits and risks in exploitation of gold and silver minerals from the Apuseni Mountains, by a Canadian majority-owned company. In 2016, mine opponents enjoyed a major victory when the village of Rosia Montana and surrounding Transylvania region were nominated to become a UNESCO World Heritage site, a designation protesters hope will secure international support and protection to the area. Still, the company continues to build the mine. Gabriel Resources is now threatening to sue the Romanian government under investment agreements for rejecting the mine. If they make good on this threat, the country could be embroiled in a World Bank tribunal trial for months.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".