Bibliographic record
Abstract
Combating poverty represents one of the challenges of the modern economy and Europe’s geopolitical situation contributes to worsening this problem. Economic growth and employment rate are determinants of the level of poverty in a society. Unemployment and its consequences are widely approached both in economic literature and in sociology and psychology. In the first part of the paper, we carried out a conceptual presentation of the economic and social consequences of unemployment at the national, individual, and family level. In the second part, starting from Okun’s law, we made an analysis of the relationship between the gross domestic product and unemployment rate for the period from 2005-2022 in Romania. In order to carry out the research, we used a series of statistical data regarding the unemployment rate available in the Monthly Bulletins of the National Bank of Romania (NBR) and data on GDP available on the website of the National Institute of Statistics of Romania (NIS). We worked with data regarding the situation in Romania from the first quarter of 2005 – fourth quarter of 2022. The conclusions of the paper converge towards the idea that unemployment is, nowadays, an increasingly complex phenomenon, being generated by a multitude of factors and which, in turn, determine multi-level direct and indirect consequences.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".