Health Care Crisis and Grassroots Social Initiative in Post-Soviet Russia
Bibliographic record
Abstract
This article analyzes the development of civil society in Russia in response to the fledging post-Soviet health care crisis. In recent years, Russian civil society has become significantly stronger and more actively engaged in public debates on social as well as political issues. This trend suggests that the process of social capital accumulation in Russia is well underway, thus instilling some hope for Russia's future. To illustrate this recent trend, I will analyze the development of two grassroots movements in St. Petersburg, which help families of children diagnosed with cancer to overcome the everyday psychological, legal and financial difficulties associated with treatment, and to lobby the government to go forward with health care reform. This paper is based on the author's personal experience as a participant in one of the grassroots initiatives, published materials in Russian journals and newspapers, and a series of interviews with volunteers. With this article, I hope to shed new light on developments in the Russian health care sector, and deepen our understanding of contemporary Russian civil society. https://doi.org/10.22215/rera.v6i1.205
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| 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".