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Record W2890840648 · doi:10.1080/17448689.2018.1518771

Volunteers in Ukraine: From provision of services to state- and nation-building

2018· article· en· W2890840648 on OpenAlexaff
Антон Олейник

Bibliographic record

VenueJournal of Civil Society · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsUkrainianDemocratizationState (computer science)Political scienceDignityNationalismSociologyPublic administrationEconomic growthPolitical economyPublic relationsDemocracyLawPolitics

Abstract

fetched live from OpenAlex

This article discusses the volunteer movement in Ukraine. After the 2013–2014 Revolution of Dignity and the subsequent military confrontation with Russia, the volunteer movement became an influential and trusted actor capable of mobilizing a large number of supporters and a significant amount of resources. Donations made to volunteer initiatives represent in Ukraine a percentage of the country's GDP similar to that seen in some Western countries. However, compared with volunteerism in developed countries, volunteer initiatives in Ukraine have several distinct features: a mostly informal character; their reliance on a hard core of committed and active leaders; and connections with the nationalist movement understood here as an actor aiming to attain and maintain the identity of the Ukrainian nation-state in the making. The article explores the intersection between warfare, nation-building, state-building and democratization using Ukraine as a case in point. Data from two sources inform the analysis: a series of in-depth qualitative interviews with leaders of the volunteer movement (N = 22) and results of a survey conducted on a representative sample (N = 2040).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.301
Teacher spread0.289 · 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 designObservational
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

Citations17
Published2018
Admission routes1
Has abstractyes

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