The Czech Labour Market: Adaptation of Young People to the Advent of Industry 4.0
Bibliographic record
Abstract
The focus of the paper was to conduct an analysis of the selected qualitative and quantitative aspects of the labour market and the potential ability of the young generation to adapt to the new conditions of their prospective employment. The primary data were obtained in the form of a questionnaire survey. The total of 2,817 respondents were contacted via email containing a research hyperlink. The respondents were secondary school students studying in the Czech Republic. The obtained data were collected in Excel and further processed by statistical methods, the Pearson test using χ quadrate. The option of choosing several occupations was evaluated by means of the so-called professional specialisation index. Secondary data were used to determine the development of trends on the Czech labour market in the current conditions of the Industry 4.0 onset. The respondents most often chose occupations in the fields of technology, industry and construction out of the eleven occupational areas offered. More than a quarter of respondents chose their preferred profession in this area. This is a positive finding in terms of the focus of the economy on Industry 4.0.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".