Adaptation of International Experience of Creation of Science Popularization Centers to Russian Realities
Bibliographic record
Abstract
Introduction. In 2021, within the framework of the Year of Science and Technology announced in Russia, the work related to the popularization of Russian science and technology plays an important role. Noticeable shifts in the field of science popularization require the selection of new forms and methods of knowledge dissemination. Interactive scientific museums and science popularization centers are called upon to play a significant role in this field. For now, a system of indicators has been developed, but it does not fully meet requirements that should be applied to the science popularization objects. The main purpose of the article is to analyze the functioning of science and technology museums, museums of natural sciences and science popularization centers in Russia and in foreign countries and, based on the study of approaches to the effectiveness of their activities, to develop approaches and tools for popularization of scientific knowledge in Russia through creation of science popularization centers and knowledge quarters. Materials and Methods. Based on the reviewed forms and methods for organization of museum functioning in China, the USA, France, Great Britain, Canada, Germany, Italy and New Zealand the museum and science popularization center (SPC) activity analysis has been conducted to understand such indicators of their activities as funding, management documents in museum functioning, criteria and procedure for museum functioning assessment, etc. This has given us the possibility to discover common features and peculiarities of museum standards of these countries. Also, primary criteria and institutions for assessment of museums and science popularization centers in Russia have been determined. Through utilization of their activity assessment documents the outstanding centers and museums of Russia have been shown, the map of museums of natural sciences and science and technology museums of our country has been developed, the recommendations to increase their activity have been prepared. Based on the method of structural analysis and synthesis, the data have been studied and summarized, which allowed creating a model as a conceptual representation of the knowledge quarter functioning, predicting new approaches and tools for popularization of science in Russia. The identified approaches in the activities of Russian and foreign museums and popularization centers have been taken into account conceptually when forming proposals for improving popularization activities in Russia. Results. With the help of the conceptual construct used to characterize museums of natural sciences, science and technology museums and science popularization centers, the basic criteria for evaluating a science popularization center in Russia have been outlined; the specifics of foreign experience that can be useful in assessing the effectiveness of an SPC in Russia has been shown; the measures have been proposed to introduce knowledge quarters as an innovative approach to popularize science in the country. Discussion and Conclusion. The work of a science popularization center should be organized at each world-class scientific and educational center and at each world-class scientific center. When implementing the new strategic academic leadership program “Priority 2030”, it is recommended to take into account the need to integrate the activities of leading universities with the activities of an SPC. The creation of a partnership of organizations based on the conceptual novel approaches for functioning of knowledge quarters working in the field of science, education and business, which are geographically located in close proximity to each other, will contribute to ensuring the influx of talented young people into science and will allow the state and society to more effectively solve the tasks of implementing state policy in the field of science, technology and innovation in the future.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".