The peculiarities of perspective students selection mechanism by the future employers-enterprise
Bibliographic record
Abstract
© 2015, Canadian Center of Science and Education. All rights reserved. The search of qualified staff is an up-to-date problem for all enterprises. In this regard the aim of the research is the development of perspective students selection mechanism by the future employers. One of the sub-stages of the algorithm is the formation of the resource and reserve groups of students by the enterprise representatives and by tutors of the faculty of professional educational institutions. The formation of the resource and reserve groups of students with flexible system of transition from one group into another according to the results of their progress, according to participation extracurricular life of the institute, participation at the international, All-Russian scientific and practical conferences, allow to intensify the process of their self-preparation by means of creation of the natural competitive environment in educational institution of professional education. It also helps to do the selection by employers and to distribute perspective students taking into account their potential opportunities and professional interests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.022 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.011 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".