Trends in Kazakhstan labor market development in the context of economy transformation
Bibliographic record
Abstract
The main employment trends are formed under the influence of structural transformations in the economy. The aim of this article is to determine the trends in the Kazakhstan labor market development in in the context of economy transformation over the past 10 years by studying the dynamics and structure of employment, depending on changes in the structure of republic’s gross domestic product. Generalization, comparison, economic-statistical (horizontal and vertical) and correlation analysis served as the main research methods. The statistical base of the study was the indicators of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan on employment and gross domestic product by type of economic activity for 2011, 2016 and 2021. During the study, it was determined that there is a pronounced (noticeable) direct statistical relationship between trends in the labor market and trends in the structure of the economy. It was revealed that the trends in labor market development in Kazakhstan are determined and depend on the trends of change and transformation of the economy structure. During the period from 2011 to 2021, the country's economy was transformed, namely, the share of the tertiary sector increased. The same trend is observed in the labor market. Thus, wholesale and retail trade, transport and warehousing, real estate transactions account for almost a third of the country's GDP. At the same time, the number of people employed in these areas is a quarter of the total number of employed. These sectors account for the highest labor productivity rates along with the mining industry. Interest in the service sector on the part of employed Kazakhstanis is growing, while in agriculture, forestry and fisheries is falling. The results of the study can serve as a scientific justification for the implementation of an effective policy in the field of labor and employment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".