Bibliographic record
Abstract
Sinikukka Saari. Promoting Democracy and Human Rights in Russia. London and New York: Routledge, 2010. xiv, 175 pp. Bibliography. Index. $130.00, cloth.Since the collapse of the Soviet Union, significant efforts have been made to promote the development of democracy and human rights in the former Soviet states. This book is a study of the efforts made by the European Union, the Council of Europe and the Organization for Security and Co-operation in Europe to encourage democracy and human rights in Russia. Sinikukka Saari focuses on three particular aspects of this question - the institution of a human rights ombudsman, abolition of the death penalty, and free and fair elections - and argues that successful promotion requires the adoption by the Russians of Western norms on these issues. She concludes that the outcome has been decidedly mixed. The norms surrounding the ombudsman have been implemented in Russia successfully in the sense that official discourse on the institution, its practical functioning and its legislative underpinning all comply with European standards. Success has been more limited with regard to the other two. While the death penalty has not actually been enforced for some time, something she attributes to European influence, it is still on the books and much of the discourse surrounding it remains supportive of its retention. With regard to free and fair elections, the European bodies have largely failed in that there has been actual regression in this respect since the first post-Soviet election in 1993; the deficient (in democratic terms) conduct of elections has become institutionalized, legislative changes in 2006-2007 actually made elections less democratic, and leading Russian figures have publicly rejected the norms of free and fair elections as understood in the West as being inappropriate for Russia.Saari' s discussion of this is competent, straightforward, and relatively unproblematic, even if at times the English expression could have done with some attention by a native speaker. Perhaps more controversial is her argument that one of the reasons for the failure in regard to free and fair elections is that the Europeans tried to play politics. She argues that during the 1990s the Europeans saw Yeltsin as the democratic hope and, believing that it was more important to support him against his opponents than it was to criticize deficiencies in electoral performance, they sought to bolster his position by overlooking the clear problems that existed in the conduct of the elections that decade. …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".