GOLD AND DISPLACEMENT IN EASTERN EUROPE: RISKS AND UNCERTAINTY AT ROŞIA MONTANĂ (English version)
Bibliographic record
Abstract
The Canadian-Romanian gold mining project at Roşia Montanǎ in Romania is known as the largest opencast gold mine being planned now in Europe. It involves the displacement of several thousand inhabitants, mostly former gold miners and a smaller number of farmers. The land and houses of more than three quarters of this population have already been acquired by the project owners, although the project has not yet received its formal environmental clearance. The paper analyzes the risks facing the displaced population of Roşia Montană, employing as analytical, methodology the Impoverishment Risks and Reconstruction (IRR) model, developed by Michael M. Cernea. The paper argues for an expansion of the IRR model. By taking into account the macro (extralocal) forces that shape displacement and paying closer attention to the micro (subjective) experience of this process, it becomes possible to understand the effects of uncertainty and vulnerability in displacement. The author’s participant observations and in-depth interviews with local families are complemented with secondary analyses of data from several other socio-economic surveys and with the analysis of the Resettlement and Relocation Action Plan of the project owners.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".