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Record W4411667314 · doi:10.18778/1508-2008.28.13

The Social and Economic Consequences of the First Year of Russia’s Fullscale Invasion of Ukraine

2025· article· en· W4411667314 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComparative Economic Research Central and Eastern Europe · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsNiagara College
Fundersnot available
KeywordsEconomic potentialEconomicsEconomic growth

Abstract

fetched live from OpenAlex

This study aims to develop an analytical framework for understanding the social and economic out­comes of Russia’s military invasion of Ukraine by studying its impact on the labor market and migration, the economy and trade, social capital, and volunteering in Ukraine. The main economic and social con­sequences include the following: the massive out-migration of refugees and internally displaced people; the change in demographic structure; the relocation and reopening of businesses and adapting to new conditions; the total collapse and de-industrialization of the occupied territories’ economy; the inter­ruption of supply chains; the reduction in trade volumes; the accumulation of social capital; and the de­velopment and spread of citizens’ volunteer cooperation to solve urgent issues at the national and lo­cal community levels. This study is limited to the available data and the effects on Ukraine’s economy and social sphere, excluding the impacts on the economies of European Union countries and the world economy in general.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
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 head0.146
GPT teacher head0.347
Teacher spread0.201 · 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