Results analysis of the regional research competition for secondary school students using information and communications technology
Bibliographic record
Abstract
The article deals with specific issues relating to the implementation of one of the priority directions of state policy of Russia is to work with gifted young people. The highly structured system of activities helped identify and develop gifted young people in science, engineering and technology and innovation development of the Samara region and allowed to define tasks and directions of the contests of students research projects in the competition "Vzlet".The article analyzes the results of the regional research competition held for the past 3 years in the Samara region for gifted secondary school students. The key quantitative indicators which may lead to further qualitative analysis were presented, specifically, the total number of participants, the number of submitted projects in different research areas, project advisors, participating educational organizations, and winning projects. In addition, the rates of those who started the competition and those who successfully completed it were analyzed. The articles offers conclusions and discusses future directions for the competition.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".