Культура производства научного знания и искусственный интеллект
Научная статья
Выражение признательности
Исследование выполнено в соответствии с государственным заданием МГУ имени М. В. Ломоносова.
Для цитирования
Тамбовцев В. Л., Рождественская И. А. Культура производства научного знания и искусственный интеллект // Управление наукой: теория и практика. 2026. Том 8. № 2. С. 135-149. DOI: https://doi.org/10.19181/smtp.2026.8.2.8 EDN: PSZPZL
Аннотация
Проведение исследований в различных отраслях, исследовательских программах и научно-исследовательских организациях осуществляется учёными в соответствии с несовпадающими правилами (методиками), а их исследовательское поведение регулируется, кроме того, неформальными институтами, сложившимися в упомянутых программах и организациях, а также индивидуальными привычками. Различные группы неформальных норм и правил образуют культуры производства научного знания, выполняющие роль того фона, на котором происходят процессы применения различных методик исследования и научных коммуникаций. Новые методы исследования могут не соответствовать сложившимся культурным нормам, что может создать затруднения в производстве научных знаний. В статье анализируется феномен искусственного интеллекта с точки зрения его соответствия некоторым аспектам культур в социальных науках и образовании. Выводы из неё свидетельствуют о продуктивности изменений, которые снизят распространённость качественных исследований и изменят формы оценки уровня компетенций, приобретаемых учащимися.
Ключевые слова:
культурные нормы, разнообразие культур производства, производство научных знаний, генеративный искусственный интеллект, оценка компетенций учащихся
Литература
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8. Merton R. K. Science and technology in democratic order. Journal of Legal and Political Sociology. 1942;1(1–2):115–126.
9. Merton R. K. Priorities in scientific discovery: A chapter in the sociology of science. American Sociological Review. 1957;22(6):635–659. DOI 10.2307/2089193.
10. Barber B. Science and the social order. Glencoe, IL : The Free Press; 1952. xxiii, 288 p.
11. Storer N. W. The social system of science. New York : Holt, Rinehart and Winston; 1966. xii, 180 p.
12. Mitroff I. I. Norms and counter-norms in a select group of the Apollo Moon scientists: A case study of the ambivalence of scientists. American Sociological Review. 1974;39(4):579–595. DOI 10.2307/2094423.
13. Anderson M. S., Ronning E. A., De Vries R., Martinson B. C. Extending the Mertonian norms: Scientists’ subscription to norms of research. The Journal of Higher Education. 2010;81(3):366–393. DOI 10.1080/00221546.2010.11779057.
14. Gopalakrishna G., Ter Riet G., Vink G., Stoop I., Wicherts J. M., Bouter L. M. Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in the Netherlands. PLoS ONE. 2022;17(2):e0263023. DOI 10.1371/journal.pone.0263023.
15. Bland C. J., Ruffin M. T. Characteristics of a productive research environment: Literature review. Academic Medicine. 1992;67(6):385–397. DOI 10.1097/00001888-199206000-00010.
16. Callard F. Towards a critical-conceptual analysis of ‘research culture’. Area. 2024;56(2):e12905. DOI 10.1111/area.12905.
17. Ajjawi R., Crampton P. E. S., Rees C. E. What really matters for successful research environments? A realist synthesis. Medical Education. 2018;52(9):936–950. DOI 10.1111/medu.13643.
18. Pawson R. Evidence-based policy: A realist perspective. London : Sage Publications; 2006. xi, 196 p. ISBN 1-84787-819-9.
19. Greenhalgh T., Wong G., Westhorp G., Pawson R. Protocol – realist and meta-narrative evidence synthesis: Evolving standards (RAMESES). BMC Medical Research Methodology. 2011;11(1):115. DOI 10.1186/1471-2288-11-115.
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21. Mazmanian P. E., Coe A. B., Evans J. A., Longo D. R., Wright B. A. Are researcher development interventions, alone or in any combination, effective in improving researcher behavior? A systematic review. Evaluation & the Health Professions. 2014;37(1):114–139. DOI 10.1177/0163278713510375.
22. Sholl S., Ajjawi R., Allbutt H., Butler J., Jindal-Snape D., Morrison J., Rees C. Balancing health care education and patient care in the UK workplace: A realist synthesis. Medical Education. 2017;51(8):787–801. DOI 10.1111/medu.13290.
23. Simula B., Scott T. The impact of pressures to produce on knowledge production and evaluation in the modern academy. Social Sciences. 2020;9(5):64. DOI 10.3390/socsci9050064.
24. Edgell R. A. A monstrous matter: The three faces of artificial creativity. Journal of Creativity. 2024;34(1):100075. DOI 10.1016/j.yjoc.2024.100075.
25. Abraham A. Why the standard definition of creativity fails to capture the creative act. Theory & Psychology. 2025;35(1):40–60. DOI 10.1177/09593543241290232.
26. Aru J. Artificial intelligence and the internal processes of creativity. Journal of Creative Behavior. 2025;59(2):e1530. DOI 10.1002/jocb.1530.
27. Da Pelo M. Artificial creativity: Can there be creativity without cognition? AI & Society. 2026;41(3):2669–2682. DOI 10.1007/s00146-025-02682-3.
28. Domanti U., Campidelli L., Agnoli S., De Angeli A. Are semantic networks associated with idea originality in artificial creativity? A comparison with human agents. In: Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26). New York : Association for Computing Machinery; 2026. Art. 1041. DOI 10.1145/3772318.3790849.
29. Runco M. A. Updating the standard definition of creativity to account for the artificial creativity of AI. Creativity Research Journal. 2025;37(1):1–5. DOI 10.1080/10400419.2023.2257977.
30. Runco M. A. The misleading definition of creativity suggested by AI must be kept out of the classroom. Education Sciences. 2025;15(9):1141. DOI 10.3390/educsci15091141.
31. Runco M. A. The discovery and innovation of AI does not qualify as creativity. Journal of Cognitive Psychology. 2024. DOI 10.1080/20445911.2024.2436362.
32. Sobetska O. Irrationality in humans and creativity in AI. Frontiers in Artificial Intelligence. 2025;8:1579704. DOI 10.3389/frai.2025.1579704.
33. Wang H., Fu T., Du Y., Gao W., Huang K., Liu Z., Chandak P., Liu S., Van Katwyk P., Deac A., Anandkumar A., Bergen K., Gomes C. P., Ho S., Kohli P., Lasenby J., Leskovec J., Liu T.-Y., Manrai A., Marks D., Ramsundar B., Song L., Sun J., Tang J., Veličković P., Welling M., Zhang L., Coley C. W., Bengio Y., Zitnik M. Scientific discovery in the age of artificial intelligence. Nature. 2023;620(7972):47–60. DOI 10.1038/s41586-023-06221-2.
34. Fonotov A. G., Bednyak Y. A. Artificial intelligence: Expected or inevitable? Science Management: Theory and Practice. 2024;6(2):15–25. (In Russ.). DOI 10.19181/smtp.2024.6.2.1. EDN EYMDJO.
35. Kulkarni M., Mantere S., Vaara E., van den Broek E., Pachidi S., Glaser V. L., Gehman J., Petriglieri G., Lindebaum D., Cameron L. D., Rahman H. A., Islam G., Greenwood M. The future of research in an artificial intelligence-driven world. Journal of Management Inquiry. 2024;33(3):207–229. DOI 10.1177/10564926231219622.
36. Osadchuk E. V. On the main trends for the development of artificial intelligence technologies as a research tool. Science Management: Theory and Practice. 2025;7(1):147–157. (In Russ.). DOI 10.19181/smtp.2025.7.1.10. EDN PHTZHX.
37. Carter L., Stone-Jovicich S., Bohensky E., Coates R., Douglas D., Ferrer-Mestres J., Harwood B., Islam M. Z., Kandanaarachchi S., McGrath M., Ong C. S., Paris C., Reeson A., Scovell M., Wissing K., Chades I. Lessons from the edges of interdisciplinarity – integrating artificial intelligence with the humanities, social and economic sciences. Applied Artificial Intelligence. 2025;39(1):2584380. DOI 10.1080/08839514.2025.2584380.
38. Li B., Gilbert S. Artificial Intelligence awarded two Nobel Prizes for innovations that will shape the future of medicine. npj Digital Medicine. 2024;7(1):336. DOI 10.1038/s41746-024-01345-9.
39. Potineni B. AI as a research accelerator: Human-AI synergy in scientific discovery and innovation. World Journal of Advanced Research and Reviews. 2025;26(1):2937–2948. DOI 10.30574/wjarr.2025.26.1.1183.
40. Mijwil M. M., Hiran K. K., Doshi R., Dadhich M., Al-Mistarehi A.-H., Bala I. ChatGPT and the future of academic integrity in the artificial intelligence era: A new frontier. Al-Salam Journal for Engineering and Technology. 2023;2(2):116–127. DOI 10.55145/ajest.2023.02.02.015.
41. Gauckler C., Werner M. H. Artificial intelligence: A challenge to scientific communication. Klinische Monatsblätter für Augenheilkunde. 2024;241(12):1309–1321. DOI 10.1055/a-2418-5238.
42. Lindebaum D., Fleming P. ChatGPT undermines human reflexivity, scientific responsibility and responsible management research. British Journal of Management. 2024;35(2):566–575. DOI 10.1111/1467-8551.12781.
43. Huang J., Tan M. The role of ChatGPT in scientific communication: Writing better scientific review articles. American Journal of Cancer Research. 2023;13(4):1148–1154.
44. Farhat K. H., Arafa M. A. The role of artificial intelligence in scientific writing. International Journal of Science and Healthcare Research. 2024;9(4):153–155. DOI 10.52403/ijshr.20240421.
45. Klein-Avraham I., Greussing E., Taddicken M., Dabran-Zivan S., Jonas E., Baram-Tsabari A. How to make sense of generative AI as a science communication researcher? A conceptual framework in the context of critical engagement with scientific information. Journal of Science Communication. 2024;23(6):A05. DOI 10.22323/2.23060205.
46. Sarker I. H. AI‑based modeling: Techniques, applications and research issues towards automation, intelligent and smart systems. SN Computer Science. 2022;3(2):158. DOI 10.1007/s42979-022-01043-x.
47. Chugunova M., Harhoff D., Hölzle K., Kaschub V., Malagimani S., Morgalla U., Rose R. Who uses AI in research, and for what? Large-scale survey evidence from Germany. Research Policy. 2026;55(2):105381. DOI 10.1016/j.respol.2025.105381.
48. Newman I., Benz C. R. Qualitative-quantitative research methodology: Exploring the interactive continuum. Carbondale ; Edwardsville, IL : Southern Illinois University Press; 1998. xiii, 218 p. ISBN 0-58517-889-5.
49. Tambovtsev V. L. Institutional analysis of economy: Qualitative and quantitative research and methods. Issues of Economic Theory=Voprosy teoreticheskoy ekonomiki. 2024;(2):45–55. (In Russ.). DOI 10.52342/2587-7666VTE_2024_2_45_55.
50. Zhou Y., Liu H., Srivastava T., Mei H., Tan C. Hypothesis generation with large language models. 2024. arXiv:2404.04326. DOI 10.48550/arXiv.2404.04326.
51. Cohrs K.-H., Diaz E., Sitokonstantinou V., Varando G., Camps-Valls G. Large language models for causal hypothesis generation in science. Machine Learning: Science and Technology. 2025;6(1):013001. DOI 10.1088/2632-2153/ada47f.
52. Joosten J., Bilgram V., Hahn A., Totzek D. Comparing the ideation quality of humans with generative artificial intelligence. IEEE Engineering Management Review. 2024;52(2):153–164. DOI 10.1109/EMR.2024.3353338.
53. Valeri F., Nilsson P., Cederqvist A. M. Exploring students’ experience of ChatGPT in STEM education. Computers and Education: Artificial Intelligence. 2025;(8):100360. DOI 10.1016/j.caeai.2024.100360.
54. Črček N., Patekar J. Writing with AI: University students’ use of ChatGPT. Journal of Language and Education. 2023;9(4):128–138. DOI 10.17323/jle.2023.17379.
2. Canti L., Chrzanowska A., Doglio M. G., Martina L., Van Den Bossche T. Research culture: Science from bench to society. Biology Open. 2021;10(8):bio058919. DOI 10.1242/bio.058919.
3. Anonymous academic. Performance-driven culture is ruining scientific research. The Guardian. 2018. February 16. Available at: https://theguardian.com/higher-education-network/2018/feb/16/performance-driven-culture-is-ruining-scientific-research (accessed: 20.04.2026).
4. Hill R. Revisiting the term “research culture”. In: Cornerstones of higher education : Papers presented at the 1999 HERDSA International conference at the University of Melbourne, July 12–15, 1999. Sydney : HERDSA; 2000. P. 1–13.
5. Schein E. H. Organizational culture and leadership: A dynamic view. San Francisco, CA : Jossey-Bass; 1985. xx, 358 p. ISBN 0-87589-639-1.
6. Kitayama S. Culture and basic psychological processes–Toward a system view of culture: Comment on Oyserman et al. (2002). Psychological Bulletin. 2002;128(1):89–96. DOI 10.1037/0033-2909.128.1.89.
7. Chiu C.-y., Leung А. K.-y., Hong Y.-y. Cultural processes: An overview. In: Leung А. K.-y., Chiu C.-y., Hong Y.-y., eds. Cultural processes: A social psychological perspective. New York : Cambridge University Press; 2011. P. 3–22. DOI 10.1017/CBO9780511779374.003.
8. Merton R. K. Science and technology in democratic order. Journal of Legal and Political Sociology. 1942;1(1–2):115–126.
9. Merton R. K. Priorities in scientific discovery: A chapter in the sociology of science. American Sociological Review. 1957;22(6):635–659. DOI 10.2307/2089193.
10. Barber B. Science and the social order. Glencoe, IL : The Free Press; 1952. xxiii, 288 p.
11. Storer N. W. The social system of science. New York : Holt, Rinehart and Winston; 1966. xii, 180 p.
12. Mitroff I. I. Norms and counter-norms in a select group of the Apollo Moon scientists: A case study of the ambivalence of scientists. American Sociological Review. 1974;39(4):579–595. DOI 10.2307/2094423.
13. Anderson M. S., Ronning E. A., De Vries R., Martinson B. C. Extending the Mertonian norms: Scientists’ subscription to norms of research. The Journal of Higher Education. 2010;81(3):366–393. DOI 10.1080/00221546.2010.11779057.
14. Gopalakrishna G., Ter Riet G., Vink G., Stoop I., Wicherts J. M., Bouter L. M. Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in the Netherlands. PLoS ONE. 2022;17(2):e0263023. DOI 10.1371/journal.pone.0263023.
15. Bland C. J., Ruffin M. T. Characteristics of a productive research environment: Literature review. Academic Medicine. 1992;67(6):385–397. DOI 10.1097/00001888-199206000-00010.
16. Callard F. Towards a critical-conceptual analysis of ‘research culture’. Area. 2024;56(2):e12905. DOI 10.1111/area.12905.
17. Ajjawi R., Crampton P. E. S., Rees C. E. What really matters for successful research environments? A realist synthesis. Medical Education. 2018;52(9):936–950. DOI 10.1111/medu.13643.
18. Pawson R. Evidence-based policy: A realist perspective. London : Sage Publications; 2006. xi, 196 p. ISBN 1-84787-819-9.
19. Greenhalgh T., Wong G., Westhorp G., Pawson R. Protocol – realist and meta-narrative evidence synthesis: Evolving standards (RAMESES). BMC Medical Research Methodology. 2011;11(1):115. DOI 10.1186/1471-2288-11-115.
20. Wong G., Greenhalgh T., Westhorp G., Pawson R. Realist methods in medical education research: What are they and what can they contribute? Medical Education. 2012;46(1):89–96. DOI 10.1111/j.1365-2923.2011.04045.x.
21. Mazmanian P. E., Coe A. B., Evans J. A., Longo D. R., Wright B. A. Are researcher development interventions, alone or in any combination, effective in improving researcher behavior? A systematic review. Evaluation & the Health Professions. 2014;37(1):114–139. DOI 10.1177/0163278713510375.
22. Sholl S., Ajjawi R., Allbutt H., Butler J., Jindal-Snape D., Morrison J., Rees C. Balancing health care education and patient care in the UK workplace: A realist synthesis. Medical Education. 2017;51(8):787–801. DOI 10.1111/medu.13290.
23. Simula B., Scott T. The impact of pressures to produce on knowledge production and evaluation in the modern academy. Social Sciences. 2020;9(5):64. DOI 10.3390/socsci9050064.
24. Edgell R. A. A monstrous matter: The three faces of artificial creativity. Journal of Creativity. 2024;34(1):100075. DOI 10.1016/j.yjoc.2024.100075.
25. Abraham A. Why the standard definition of creativity fails to capture the creative act. Theory & Psychology. 2025;35(1):40–60. DOI 10.1177/09593543241290232.
26. Aru J. Artificial intelligence and the internal processes of creativity. Journal of Creative Behavior. 2025;59(2):e1530. DOI 10.1002/jocb.1530.
27. Da Pelo M. Artificial creativity: Can there be creativity without cognition? AI & Society. 2026;41(3):2669–2682. DOI 10.1007/s00146-025-02682-3.
28. Domanti U., Campidelli L., Agnoli S., De Angeli A. Are semantic networks associated with idea originality in artificial creativity? A comparison with human agents. In: Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26). New York : Association for Computing Machinery; 2026. Art. 1041. DOI 10.1145/3772318.3790849.
29. Runco M. A. Updating the standard definition of creativity to account for the artificial creativity of AI. Creativity Research Journal. 2025;37(1):1–5. DOI 10.1080/10400419.2023.2257977.
30. Runco M. A. The misleading definition of creativity suggested by AI must be kept out of the classroom. Education Sciences. 2025;15(9):1141. DOI 10.3390/educsci15091141.
31. Runco M. A. The discovery and innovation of AI does not qualify as creativity. Journal of Cognitive Psychology. 2024. DOI 10.1080/20445911.2024.2436362.
32. Sobetska O. Irrationality in humans and creativity in AI. Frontiers in Artificial Intelligence. 2025;8:1579704. DOI 10.3389/frai.2025.1579704.
33. Wang H., Fu T., Du Y., Gao W., Huang K., Liu Z., Chandak P., Liu S., Van Katwyk P., Deac A., Anandkumar A., Bergen K., Gomes C. P., Ho S., Kohli P., Lasenby J., Leskovec J., Liu T.-Y., Manrai A., Marks D., Ramsundar B., Song L., Sun J., Tang J., Veličković P., Welling M., Zhang L., Coley C. W., Bengio Y., Zitnik M. Scientific discovery in the age of artificial intelligence. Nature. 2023;620(7972):47–60. DOI 10.1038/s41586-023-06221-2.
34. Fonotov A. G., Bednyak Y. A. Artificial intelligence: Expected or inevitable? Science Management: Theory and Practice. 2024;6(2):15–25. (In Russ.). DOI 10.19181/smtp.2024.6.2.1. EDN EYMDJO.
35. Kulkarni M., Mantere S., Vaara E., van den Broek E., Pachidi S., Glaser V. L., Gehman J., Petriglieri G., Lindebaum D., Cameron L. D., Rahman H. A., Islam G., Greenwood M. The future of research in an artificial intelligence-driven world. Journal of Management Inquiry. 2024;33(3):207–229. DOI 10.1177/10564926231219622.
36. Osadchuk E. V. On the main trends for the development of artificial intelligence technologies as a research tool. Science Management: Theory and Practice. 2025;7(1):147–157. (In Russ.). DOI 10.19181/smtp.2025.7.1.10. EDN PHTZHX.
37. Carter L., Stone-Jovicich S., Bohensky E., Coates R., Douglas D., Ferrer-Mestres J., Harwood B., Islam M. Z., Kandanaarachchi S., McGrath M., Ong C. S., Paris C., Reeson A., Scovell M., Wissing K., Chades I. Lessons from the edges of interdisciplinarity – integrating artificial intelligence with the humanities, social and economic sciences. Applied Artificial Intelligence. 2025;39(1):2584380. DOI 10.1080/08839514.2025.2584380.
38. Li B., Gilbert S. Artificial Intelligence awarded two Nobel Prizes for innovations that will shape the future of medicine. npj Digital Medicine. 2024;7(1):336. DOI 10.1038/s41746-024-01345-9.
39. Potineni B. AI as a research accelerator: Human-AI synergy in scientific discovery and innovation. World Journal of Advanced Research and Reviews. 2025;26(1):2937–2948. DOI 10.30574/wjarr.2025.26.1.1183.
40. Mijwil M. M., Hiran K. K., Doshi R., Dadhich M., Al-Mistarehi A.-H., Bala I. ChatGPT and the future of academic integrity in the artificial intelligence era: A new frontier. Al-Salam Journal for Engineering and Technology. 2023;2(2):116–127. DOI 10.55145/ajest.2023.02.02.015.
41. Gauckler C., Werner M. H. Artificial intelligence: A challenge to scientific communication. Klinische Monatsblätter für Augenheilkunde. 2024;241(12):1309–1321. DOI 10.1055/a-2418-5238.
42. Lindebaum D., Fleming P. ChatGPT undermines human reflexivity, scientific responsibility and responsible management research. British Journal of Management. 2024;35(2):566–575. DOI 10.1111/1467-8551.12781.
43. Huang J., Tan M. The role of ChatGPT in scientific communication: Writing better scientific review articles. American Journal of Cancer Research. 2023;13(4):1148–1154.
44. Farhat K. H., Arafa M. A. The role of artificial intelligence in scientific writing. International Journal of Science and Healthcare Research. 2024;9(4):153–155. DOI 10.52403/ijshr.20240421.
45. Klein-Avraham I., Greussing E., Taddicken M., Dabran-Zivan S., Jonas E., Baram-Tsabari A. How to make sense of generative AI as a science communication researcher? A conceptual framework in the context of critical engagement with scientific information. Journal of Science Communication. 2024;23(6):A05. DOI 10.22323/2.23060205.
46. Sarker I. H. AI‑based modeling: Techniques, applications and research issues towards automation, intelligent and smart systems. SN Computer Science. 2022;3(2):158. DOI 10.1007/s42979-022-01043-x.
47. Chugunova M., Harhoff D., Hölzle K., Kaschub V., Malagimani S., Morgalla U., Rose R. Who uses AI in research, and for what? Large-scale survey evidence from Germany. Research Policy. 2026;55(2):105381. DOI 10.1016/j.respol.2025.105381.
48. Newman I., Benz C. R. Qualitative-quantitative research methodology: Exploring the interactive continuum. Carbondale ; Edwardsville, IL : Southern Illinois University Press; 1998. xiii, 218 p. ISBN 0-58517-889-5.
49. Tambovtsev V. L. Institutional analysis of economy: Qualitative and quantitative research and methods. Issues of Economic Theory=Voprosy teoreticheskoy ekonomiki. 2024;(2):45–55. (In Russ.). DOI 10.52342/2587-7666VTE_2024_2_45_55.
50. Zhou Y., Liu H., Srivastava T., Mei H., Tan C. Hypothesis generation with large language models. 2024. arXiv:2404.04326. DOI 10.48550/arXiv.2404.04326.
51. Cohrs K.-H., Diaz E., Sitokonstantinou V., Varando G., Camps-Valls G. Large language models for causal hypothesis generation in science. Machine Learning: Science and Technology. 2025;6(1):013001. DOI 10.1088/2632-2153/ada47f.
52. Joosten J., Bilgram V., Hahn A., Totzek D. Comparing the ideation quality of humans with generative artificial intelligence. IEEE Engineering Management Review. 2024;52(2):153–164. DOI 10.1109/EMR.2024.3353338.
53. Valeri F., Nilsson P., Cederqvist A. M. Exploring students’ experience of ChatGPT in STEM education. Computers and Education: Artificial Intelligence. 2025;(8):100360. DOI 10.1016/j.caeai.2024.100360.
54. Črček N., Patekar J. Writing with AI: University students’ use of ChatGPT. Journal of Language and Education. 2023;9(4):128–138. DOI 10.17323/jle.2023.17379.
Статья
Поступила: 25.02.2026
Опубликована: 25.06.2026
Форматы цитирования
Другие форматы цитирования:
APA
Тамбовцев, В. Л., & Рождественская, И. А. (2026). Культура производства научного знания и искусственный интеллект. Управление наукой: теория и практика, 8(2), 135-149. https://doi.org/10.19181/smtp.2026.8.2.8
Раздел
Информационная среда и проблемы цифровизации
JATS XML
