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Record W2084961526 · doi:10.1017/s000842390535997x

Building Democracy in Contemporary Russia: Western Support for Grassroots Organizations

2005· article· en· W2084961526 on OpenAlexaff
Juliet Johnson

Bibliographic record

VenueCanadian Journal of Political Science · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsGrassrootsCivil societyBureaucracyDemocracyElitePolitical sciencePublic administrationEconomic growthSociologyPoliticsLawEconomics

Abstract

fetched live from OpenAlex

Building Democracy in Contemporary Russia: Western Support for Grassroots Organizations , Sarah L. Henderson, Ithaca: Cornell University Press, 2003, pp. xii, 229. In this well-researched and provocative book, Sarah Henderson asks to what extent Western aid can facilitate the emergence of civil society in countries where civil society is domestically weak. Through an in-depth study of Western aid to Russian women's organizations, she argues that foreign assistance has dramatically affected NGO development in Russia, but not always in expected or positive ways. On the one hand, she finds that external funding “made a tremendous difference in improving and increasing the short-term financial viability, organizational capacity, and networking skills among recipient groups” (9). On the other, she argues that foreign aid contributed to at least four pathological developments within the NGO community. First, funded groups tended to copy the aid agencies' top-heavy and bureaucratic organizational structures. Second, funded groups lacked grassroots constituencies because they shifted their policy agendas to reflect aid agencies' preferences rather than objective domestic needs. Third, foreign aid encouraged the development of a “civic elite” among the domestic NGO community, exacerbating the differences between those groups that received funding and those that did not. Finally, the competition for foreign aid dollars encouraged uncooperative behaviour among funded Russian NGOs rather than bridge building and information sharing. She argues that these problematic unintended consequences were the result of avoidable mistakes in the foreign aid process, and states bluntly that “NGO development is not synonymous with civil society development, and the development of one does not necessarily imply the advancement of the other” (11).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.350
Teacher spread0.311 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2005
Admission routes1
Has abstractyes

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