The Impact of External, Legal, and Socio-Economic Environment on the Well-Being of Pensioners in Kosovo: A Generalized Linear Model (GLM) Approach
Bibliographic record
Abstract
The study analyzes the well-being of contributory pensioners in Kosovo, focusing on financial, legal, and emotional aspects.Kosovar pensioners face low incomes and weak pension legislation.To address this issue, a structured questionnaire was randomly distributed to contributory pensioners across Kosovo.The data were analyzed using SPSS software.To ensure the validity and reliability of the Generalized Linear Model (GLM), statistical tests such as Cronbach's Alpha, Hotelling's T-Squared, Breusch-Pagan test, KMO & Bartlett's Test, and Principal Component Analysis (PCA) were employed.The study evaluated four hypotheses examining various factors influencing the well-being of contributory pensioners in Kosovo.H1 explored administrative and legal variables.The results indicated that regular reporting to the Pension Administration (RE6MPC) had a borderline positive impact on well-being (β = 0.803, p = 0.051), while the perception that the State Very Active (SVA) had a significant positive effect (β = 1.016, p = 0.016).Legal Reform (LR), however, showed a significant negative impact (β = -0.912,p = 0.039).H2 focused on financial variables, but none of the predictors-including pension increase and support for medications-were statistically significant.H3 assessed health and lifestyle factors, finding that hobbies and walking were significantly and positively associated with well-being (p < 0.01), while poor health negatively impacted well-being (β = -0.566,p = 0.017); marital status was not significant.H4 utilized Pearson correlation analysis, revealing that variables such as marital status, health, and perceived state activity were positively and significantly associated with well-being, while Equal Evaluation of Contributory and Non-Contributory Pensions (EECNCP) had a significant negative correlation (r = -0.370,p = 0.008).Overall, the results partially support H1 and H4, fully support H3, and do not support H2.The recommendations include strengthening health and social support, increasing state commitment, ensuring equality in the treatment of pensioners, and increasing the contributory pension category.Originality, this is the first study to measure the well-being of contributory pensioners in Kosovo through the GLM approach and to identify socio-emotional-legal factors as more important than financial factors even though the pension does not exceed 318 euros as of 2025.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".