Mediated risks: the Roşia Montană displacement and a new perspective on the IRR model
Bibliographic record
Abstract
The impoverishment risks and reconstruction (IRR) model is widely used in research on involuntary population displacements. This article endorses an expansion of the model to better account for how impoverishment risks are mediated through economic circumstances and through actors outside and within the displacement process. The case of the proposed Roşia Montană mining project in Romania reveals that some impoverishment risks originate beyond displacement itself, and are harder to counter, while others are mitigated through local resistance and the strategic deployment of material and cultural assets. The Roşia Montană displacement also shows that mediation reduces the predictability of IRR risks.Résumé Le modèle IRR (Impoverishment Risks and Reconstruction) est largement utilisé dans la recherche sur les déplacements involontaires de populations. Cet article propose une extension de ce modèle pour mieux tenir compte du rôle que joue la situation économique locale et celui des acteurs qui participent, de l'intérieur comme de l'extérieur, au processus de déplacement. Le projet minier Roşia Montană en Roumanie montre que certains risques d'appauvrissement, plus difficiles à contrer, ne proviennent pas du déplacement lui-même. D'autres risques sont atténués grâce à la résistance locale et au déploiement stratégique, par les collectivités touchées, de leurs ressources matérielles et culturelles. Dans le cas étudié, ces facteurs de médiation limitent la puissance prédictive du modèle IRR.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".