MétaCan
Menu
Back to cohort
Record W4281667734 · doi:10.1177/08883254211070851

The Evolution of Civic Activism in Contemporary Russia

2022· article· en· W4281667734 on OpenAlexaff
Lisa McIntosh Sundstrom, Laura A. Henry, Valerie Sperling

Bibliographic record

VenueEast European Politics and Societies and Cultures · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnvironmentalismPolitical activismSocial activismProfessionalizationPoliticsCivil societyPolitical sciencePolitical economySociologyPublic administrationPublic relationsLaw

Abstract

fetched live from OpenAlex

This article examines Russian citizens’ support for and participation in civic activism today, nearly three decades after the collapse of the Soviet Union. Specifically, we consider how activism has evolved over time in two key issue sectors—environmentalism and women’s rights. We draw on a recent nationally representative survey that challenges existing stereotypes of Russians as apathetic and/or fearful of participating in civic activism, showing, to the contrary, that Russians are willing and interested in engaging in public activities. Data from field interviews with environmental and feminist activists, along with the authors’ past twenty-five years of research in these areas of Russian civic activism, allow us to identify an ongoing shift from professionalization and formalization of NGOs in the 1990s and early 2000s, to informal organizing, often assisted by social media platforms, today. We argue that the three major social and political drivers of this change in Russian civic activism are the contraction of political freedoms, the decline in foreign funding, and the availability of web-based communication and fundraising technologies.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.285
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEast European Politics and Societies and CulturesSame topicReligion and Society InteractionsFrench-language works237,207