Professional Consciousness as a Subjective Component of a Personal Professional Development
Bibliographic record
Abstract
The study discusses the professional development of the individual, which is a multi-faceted process. The relevance of this work is defined by development trends that radically change the essence of professions on the labour market and require an understanding of the role of career guidance and professional self-determination as a single process throughout the entire working life of an individual. The study aims to investigate professional consciousness as a subjective component of professionalism and consider the algorithm for the development of professional self-consciousness in society. The study covers the main stages of professional development of the individual as a single process. The analysis of documents (monographs, websites, statistics, academic papers, and textbooks) was the objective method for the study. The study researched and systematised the leading approaches to discovering personal potential based on the collected material and identified all types of professional competence using the analysis method. As a result, the definition of factors of professionalism creates mental models of professional activity and the professional self-consciousness of the individual. The practical value of the study discussed and analysed the stages of development and establishment of a professional individual is implementing the results in the educational process and using the provided recommendations for creating a personal programme for mastering the course on the psychology of personality and professional development.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".