Current state and problems of vocational guidance of young people in Ukraine and Canada
Bibliographic record
Abstract
The article highlights the relevance of carrying out work on career guidance among the population and the importance of creating an effective system of vocational guidance. The brief history of the background of the birth and formation of vocational guidance in Ukraine and career development in Canada as well as the construction of a state system of professional orientation in these countries at the present stage are presented in this thesis. The concept of professional orientation as a system of interrelated economic, social, medical, psychological and pedagogical measures directed on activation of the process of professional self-determination of the person is presented. The views of modern scholars on the problems of professional orientation in Ukraine are analyzed. The activity of the government and public organizations in the field of career guidance of the population is explored. It is concluded that in Ukraine today there is no general vision of the development of professional orientation and clear quality criteria and a system of measurement of the effectiveness of providing vocational guidance services, and state bodies provide unsystematic services for professional orientation to different segments of the population. The essence of the concept of Career Development is the lifelong process of managing learning, work, leisure, and transitions in order to move towards a personally determined and evolving preferred future. It has been found that in Canada one notices a convergence of four sectors of society: government, education, organized labor and the non-profit-making sector. It has been established that a number of state, non-governmental and international organizations and projects have been created and effectively functioning in Canada’s Career Development, and their effective interaction has allowed to strengthen and develop a career development and career guidance. The role of career tutors using the latest career development strategies adapted to the diverse population of Canada is highlighted. A number of differences in the vocational guidance of Ukraine and Canada are revealed, which is connected with different historical, social and economic development of the countries.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".