Accumulation by Dispossession: An Analysis of Social and Economic Reforms in Ukraine
Bibliographic record
Abstract
My dissertation examines the impact of neoliberal reforms on the socioeconomic sphere in post-Soviet Ukraine, and discusses their implications for the standard of living of citizens.The independence of Ukraine from the USSR initiated the ascendance of a very affluent Ukrainian capitalist class in a short period of time.The disassembly of socialist welfare, however, took much longer.I introduce the concept of "socialist residualism" to make sense of the resistance to neoliberal encroachments on Ukraine's institutions and social logics.I trace socialist residualism through several distinct periods in independent Ukraine, as the introduction of capitalism there was imbued with unique characteristics that differed from post-Soviet states that moved much faster to shed their socialist social and economic relations.The events of 2014 marked an institutional rupture accelerating the accumulation by dispossession of public and state assets, and strengthened the recommodification of labour and the social sphere.I employed semi-structured interviews to investigate changes to Ukrainians' socioeconomic welfare in the Central and Western regions of Ukraine in the periods from 2016 to 2022.My first case study analyses the changes to social reproduction in the rural and agricultural region, including the development of land as a form of social security for women and their families.The second case study explores the loss of a wide range of public services associated with the dismantlement of a city-forming enterprise, which impacted the city as a whole, and its residents, in particular.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".