Bibliographic record
Abstract
By challenging the state and corporate prerogatives to distinguish between “good” and “bad” development, social movements by and in support of inhabitants of Rosia Montana (Transylvania) are subverting prevailing perceptions about Central and Eastern Europe (CEE)’s liberal path of development illustrating its injustice in several ways that will be detailed in this article under the heading “inhibitions of political economy” or Balkanism. The significance of the “Save Rosia Montana” movement for post-communism is that it invites post-communist subjects to reflect and revise their perception about issues such as communism, capitalism and development and to raise questions of global significance about the fragile edifice of justice within the neo-liberal capitalist economy. However, resistance to injustice (and implicitly affirmations of other senses of justice) is an ambiguous discursive practice through which Rosieni make sense as well as partake their sense of Rosia Montana. The movement brings about a public dispute which may be compared with a differend: (in Lyotard’s words), a conflict that cannot be confined to the rules of “cognitive phrases,” of truth and falsehood. This article argues that while post-communist events of “subjectification” are unstable and thus, are to be viewed aesthetically, this same ambiguous multiplication of political subjectivity may facilitate the creation of social spaces for imagining alternative possibilities of development.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".