Features of Formation of Future Educational Psychologists’ Professional Identity during Their Retraining
Bibliographic record
Abstract
The actuality of the problem’s research is caused by conditions of three kinds: firstly, the increasing demand for the profession and humanistic values of the practical psychologist in education; secondly, the special circumstances of the accelerated training of psychologists (from former teachers), who are actually taking possession of a new profession; thirdly, the lack of research, where the impact of training on professional identity is studied. The purpose of the article is to uncover the structure of future educational psychologists’ professional notions, identifying the occurrence period of their basic elements (“standard frame”) of professional-psychological picture of the world, establishing the peculiarities of professional outlook. The leading method of study of this problem is ascertaining experiment. As a result the structure and genesis of professional psychological image of the world of the future educational psychologists was revealed. The materials of the article are of great value to the organizers of professional retraining of educational psychologists, academics, as well as valuable in the development of recommendations regarding formation of policies in the sphere of additional education in “Practical Psychology in Education”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".