Bibliographic record
Abstract
Background. The study is devoted to a comprehensive analysis of the reintegration process of veterans with disabilities into civilian life at the current stage of Ukrainian society's development. The concept of “reintegration of demobilized veterans with disabilities” is analyzed through the scientific approaches of sociology, psychology, law, and social work, which makes it possible to determine the interdisciplinary nature of the problem. Methods. The study includes an analysis of Ukraine's current legal and regulatory framework for supporting veterans with disabilities, a comparative examination of international experience (USA, Israel, Canada), and the identification of key directions for implementing reintegration. Methods of system analysis, comparison, and generalization were applied. Results. The study revealed the strengths and weaknesses of the national system for supporting veterans with disabilities. The main directions of the reintegration process and the barriers that hinder veterans' full return to civilian life were identified. Based on international experience, recommendations were proposed for improving the national system of social assistance and rehabilitation for veterans. Conclusions. Effective reintegration of veterans with disabilities requires a systemic and individualized approach that involves coordination between state institutions, civil society organizations, and the veterans themselves. The results of the study can be used to develop practical recommendations for improving veteran support policies, creating programs for social adaptation, professional rehabilitation, and psychological assistance. The work contributes to a deeper understanding of the complexity and multifaceted nature of the reintegration process of veterans with disabilities in modern conditions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".