A Battery of Measures for Psychometric Assessment of Life History Strategy

封面

如何引用文章

全文:

详细

In recent years, life history theory has significantly strengthened its position in the social sciences, offering explanations for persistent variations in behavior and values, as well as physiological, cognitive, psychological, and social traits of individuals along the continuum between fast and slow strategies. In this paper, we present a comprehensive overview of this all-encompassing theory, demonstrating its significance across various disciplines. Psychometric methods for assessing life history strategy (LHS) are typically based on the evaluation of the so-called K -factor, where a high value indicates a slower LHS and, conversely, a lower value indicates a faster LHS. In our study, we were adapting and validating the most popular unidimensional measure, the so-called Mini-K, for the Russian context, supplementing it with our measure for assessing the harshness of childhood conditions (threats, deprivations, unpredictability), which allows us to overcome the limitations of the original approach. The first stage of development and adaptation involved a qualitative analysis of the measures’ content using cognitive interviews. These interviews supported the adequacy of the item formulations for the Russian-speaking context, as well as their accuracy and clarity. In the second stage, an empirical validation of the methods was conducted through a sociopsychological survey involving 2,032 Russians. The results showed that the proposed factor structure for both measures possesses optimal global fit with the measurement models. The scales demonstrated sex invariance, high reliability coefficients, as well as convergent and discriminant validity. Considering previous research on the psychometric assessment of LHS, the Mini-K method demonstrated adequate results that are substantively related to the measure assessing the harshness of childhood conditions and some biodemographic indicators. The proposed measures will be especially useful for studies dedicated to examining individual and group differences.

作者简介

Elizaveta Komyaginskaya

HSE University

编辑信件的主要联系方式.
Email: ekomyaginskaya@hse.ru
ORCID iD: 0000-0002-8841-1722
SPIN 代码: 4854-0374
Scopus 作者 ID: 59204492200
Researcher ID: HII-5216-2022

Research Intern, Center for Sociocultural Research

20 Myasnitskaya St, Moscow, 101000, Russian Federation

Albina Gallyamova

HSE University

Email: aagallyamova@hse.ru
ORCID iD: 0000-0002-8775-7289
SPIN 代码: 6639-2529
Scopus 作者 ID: 58182813400
Researcher ID: GLV-6876-2022

Junior Research Fellow, Center for Sociocultural Research

20 Myasnitskaya St, Moscow, 101000, Russian Federation

Alisa Godovanets

HSE University

Email: agodovanets@hse.ru
ORCID iD: 0009-0004-3953-3303
Researcher ID: JLM-1622-2023

Research Intern, Institute for Cognitive Neuroscience

20 Myasnitskaya St, Moscow, 101000, Russian Federation

Dmitry Grigoryev

HSE University

Email: dgrigoryev@hse.ru
ORCID iD: 0000-0003-4511-7942
SPIN 代码: 1807-9739
Scopus 作者 ID: 57191706675
Researcher ID: K-3338-2015

Research Fellow, Center for Sociocultural Research

20 Myasnitskaya St, Moscow, 101000, Russian Federation

参考

  1. Vasilieva, N.A. (2021). Pace-of-life syndrome (pols): Evolution of the theory. Zoologicheskii zhurnal, 100(9), 969–983. (In Russ.) https://doi.org/10.31857/s0044513421090117
  2. Aunger, R., Gallyamova, A., & Grigoryev, D. (2025). Network psychometric-based identification and structural analysis of a set of evolved human motives. Personality and Individual Differences, 233, 112921. https://doi.org/10.1016/j.paid.2024.112921
  3. Baldini, R. (2015). The importance of population growth and regulation in human life history evolution. PLOS ONE, 10(4), e0119789. https://doi.org/10.1371/journal.pone.0119789
  4. Belsky, J., Steinberg, L., & Draper, P. (1991). Childhood experience, interpersonal development, and reproductive strategy: An evolutionary theory of socialization. Child Development, 62(4), 647–670. https://doi.org/10.2307/1131166
  5. Brooks, R.C., & Garratt, M.G. (2017). Life history evolution, reproduction, and the origins of sex-dependent aging and longevity. Annals of the New York Academy of Sciences, 1389(1), 92–107. https://doi.org/10.1111/nyas.13302
  6. Brumbach, B.H., Figueredo, A.J., & Ellis, B.J. (2009). Effects of harsh and unpredictable environments in adolescence on development of life history strategies. Human Nature, 20(1), 25–51. https://doi.org/10.1007/s12110-009-9059-3
  7. Caswell, H. (2007). Extrinsic mortality and the evolution of senescence. Trends in Ecology & Evolution, 22(4), 173–174. https://doi.org/10.1016/j.tree.2007.01.006
  8. Chang, L., Lu, H.J., Lansford, J.E., Skinner, A.T., Bornstein, M.H., Steinberg, L., Dodge, K.A., Chen, B.B., Tian, Q., Bacchini, D., Deater-Deckard, K., Pastorelli, C., Alampay, L.P., Sorbring, E., Al-Hassan, S.M., Oburu, P., Malone, P.S., Di Giunta, L., Tirado, L.M.U., & Tapanya, S. (2019). Environmental harshness and unpredictability, life history, and social and academic behavior of adolescents in nine countries. Developmental Psychology, 55(4), 890–903. https://doi.org/10.1037/dev0000655
  9. Copping, L.T., Campbell, A., & Muncer, S. (2014). Psychometrics and life history strategy: the structure and validity of the high k strategy scale. Evolutionary Psychology, 12(1), 200–222. https://doi.org/10.1177/147470491401200115
  10. Dantzer, B., & Swanson, E.M. (2017). Does hormonal pleiotropy shape the evolution of performance and life history traits? Integrative and Comparative Biology, 57(2), 372–384. https://doi.org/10.1093/icb/icx064
  11. Del Giudice, M. (2020). Rethinking the fast-slow continuum of individual differences. Evolution and Human Behavior, 41(6), 536–549. https://doi.org/10.1016/j.evolhumbehav. 2020.05.004
  12. Del Giudice, M. (2025). A turning point for the life history approach to individual differences. In S. Kanazawa (Ed.). Genes, Environments, and Differential Susceptibility: Current Topics in Evolutionary Developmental Psychology (pp. 1-25). Cambridge: Cambridge University Press.
  13. Del Giudice, M., Ellis, B.J., & Shirtcliff, E.A. (2011). The adaptive calibration model of stress responsivity. Neuroscience & Biobehavioral Reviews, 35(7), 1562–1592. https://doi.org/10.1016/j.neubiorev.2010.11.007
  14. Ding, W., Xu, Y., Kondracki, A.J., & Sun, Y. (2024). Childhood adversity and accelerated reproductive events: a systematic review and meta-analysis. American Journal of Obstetrics and Gynecology, 230(3), 315-329.e31. https://doi.org/10.1016/j.ajog. 2023.10.005
  15. Ellis, B. J. (2004). Timing of pubertal maturation in girls: An integrated life history approach. Psychological Bulletin, 130(6), 920–958. https://doi.org/10.1037/0033-2909.130.6.920
  16. Ellis, B.J., Figueredo, A.J., Brumbach, B.H., & Schlomer, G.L. (2009). Fundamental dimensions of environmental risk: The impact of harsh versus unpredictable environments on the evolution and development of life history strategies. Human Nature, 20(2), 204–268. https://doi.org/10.1007/s12110-009-9063-7
  17. Ellis, B.J., Reid, B.M., & Kramer, K.L. (2024). Two tiers, not one: Different sources of extrinsic mortality have opposing effects on life history traits. Behavioral and Brain Sciences, 1–75. https://doi.org/10.1017/s0140525x24001316
  18. Ellis, B.J., Sheridan, M.A., Belsky, J., & McLaughlin, K.A. (2022). Why and how does early adversity influence development? Toward an integrated model of dimensions of environmental experience. Development and Psychopathology, 34(2), 447–471. https://doi.org/10.1017/s0954579421001838
  19. Ellison, P.T. (2017). Endocrinology, energetics, and human life history: A synthetic model. Hormones and Behavior, 91, 97–106. https://doi.org/10.1016/j.yhbeh.2016.09.006
  20. Erickson, L.C., & Newman, R.S. (2017). Influences of background noise on infants and children. Current Directions in Psychological Science, 26(5), 451–457. https://doi.org/ 10.1177/0963721417709087
  21. Figueredo, A., Vasquez, G., Brumbach, B., Schneider, S., Sefcek, J., Tal, I., Hill, D., Wenner, C., & Jacobs, W. (2006). Consilience and life history theory: From genes to brain to reproductive strategy. Developmental Review, 26(2), 243–275. https://doi.org/10.1016/j.dr.2006.02.002
  22. Figueredo, A.J., Cabeza de Baca, T., & Woodley, M.A. (2013a). The measurement of human life history strategy. Personality and Individual Differences, 55(3), 251–255. https:// doi.org/10.1016/j.paid.2012.04.033
  23. Figueredo, A.J., de Baca, T.C., Black, C.J., García, R.A., Fernandes, H.B.F., Wolf, P.S.A., & Anthony, M. (2015). Methodologically sound: Evaluating the psychometric approach to the assessment of human life history [Reply to Copping, Campbell, and Muncer, 2014]. Evolutionary Psychology, 13(2), 299–338. https://doi.org/10.1177/147470491501300202
  24. Figueredo, A.J., Garcia, R.A., Menke, J.M., Jacobs, W.J., Gladden, P.R., Bianchi, J., Patch, E.A., Beck, C.J.A., Kavanagh, P.S., Sotomayor-Peterson, M., Jiang, Y., & Li, N.P. (2017). The K-SF-42. Evolutionary Psychology, 15(1). https://doi.org/10.1177/ 1474704916676276
  25. Figueredo, A.J., Hertler, S.C., & Peñaherrera-Aguirre, M. (2021). The biogeography of human diversity in cognitive ability. Evolutionary Psychological Science, 7(2), 106–123. https://doi.org/10.1007/s40806-020-00267-5
  26. Figueredo, A.J., Vásquez, G., Brumbach, B.H., & Schneider, S.M.R. (2004). The heritability of life history strategy: The k-factor, covitality, and personality. Biodemography and Social Biology, 51(3–4), 121–143. https://doi.org/10.1080/19485565.2004.9989090
  27. Figueredo, A.J., Vásquez, G., Brumbach, B.H., & Schneider, S.M.R. (2007). The K-factor, covitality, and personality. Human Nature, 18(1), 47–73. https://doi.org/10.1007/bf02820846
  28. Figueredo, A.J., Vásquez, G., Brumbach, B.H., Sefcek, J.A., Kirsner, B.R., & Jacobs, W.J. (2005). The K-factor: Individual differences in life history strategy. Personality and Individual Differences, 39(8), 1349–1360. https://doi.org/10.1016/j.paid.2005.06.009
  29. Figueredo, A.J., Wolf, P.S.A., Olderbak, S.G., Gladden, P.R., Fernandes, H.B.F., Wenner, C., Hill, D., Andrzejczak, D.J., Sisco, M.M., Jacobs, W.J., Hohman, Z.J., Sefcek, J.A., Kruger, D., Howrigan, D.P., MacDonald, K., & Rushton, J.P. (2014). The psychometric assessment of human life history strategy: A meta-analytic construct validation. Evolutionary Behavioral Sciences, 8(3), 148–185. https://doi.org/10.1037/h0099837
  30. Figueredo, A.J., Woodley, M.A., Brown, S.D., & Ross, K.C. (2013b). Multiple successful tests of the strategic differentiation-integration effort (SD-IE) hypothesis. Journal of Social, Evolutionary, and Cultural Psychology, 7(4), 361–383. https://doi.org/10.1037/h0099182
  31. Frankenhuis, W.E., & Nettle, D. (2020). Current debates in human life history research. Evolution and Human Behavior, 41(6), 469–473. https://doi.org/10.1016/j.evolhumbehav.2020.09.005
  32. Gallyamova, A., Komyaginskaya, E., Vasyunina, A., & Grigoryev, D. (2025). Demography and culture in Russia: Life history trade-offs in regional differences. Population and Economics, 9(1), 155–172. https://doi.org/10.3897/popecon.9.e139731
  33. Grebe, N.M., Del Giudice, M., Emery Thompson, M., Nickels, N., Ponzi, D., Zilioli, S., Maestripieri, D., & Gangestad, S.W. (2019). Testosterone, cortisol, and status-striving personality features: A review and empirical evaluation of the Dual Hormone hypothesis. Hormones and Behavior, 109, 25–37. https://doi.org/10.1016/j.yhbeh.2019.01.006
  34. Gurven, M.D. (2024). Life History. In J. Koster, B. Scelza, M.K. Shenk (Eds.). Human Behavioral Ecology (pp. 20–47). Cambridge: Cambridge University Press. https:// doi.org/10.1017/9781108377911.003
  35. Hartman, S., Sung, S., Simpson, J.A., Schlomer, G.L., & Belsky, J. (2018). Decomposing environmental unpredictability in forecasting adolescent and young adult development: A two-sample study. Development and Psychopathology, 30(4), 1321–1332. https:// doi.org/10.1017/s0954579417001729
  36. Healy, K., Ezard, T.H.G., Jones, O.R., Salguero-Gómez, R., & Buckley, Y.M. (2019). Animal life history is shaped by the pace of life and the distribution of age-specific mortality and reproduction. Nature Ecology & Evolution, 3(8), 1217–1224. https://doi.org/10.1038/s41559-019-0938-7
  37. Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  38. Hertler, S., de Baca, T.C., Peñaherrera-Aguirre, M., Fernandes, H.B.F., & Figueredo, A.J. (2021). Life history evolution forms the foundation of the adverse childhood experience pyramid. Evolutionary Psychological Science, 8(1), 89–104. https://doi.org/10.1007/s40806-021-00299-5
  39. Kaplan, H., Hill, K., Lancaster, J., & Hurtado, A.M. (2000). A theory of human life history evolution: Diet, intelligence, and longevity. Evolutionary Anthropology: Issues, News, and Reviews, 9(4), 156–185. https://doi.org/10.1002/1520-6505(2000)9:4<156::aid-evan5>3.0.co;2-7
  40. Kline, R.B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.
  41. Leiby, J., & Madsen, P.E. (2017). Margin of safety: Life history strategies and the effects of socioeconomic status on self-selection into accounting. Accounting, Organizations and Society, 60, 21–36. https://doi.org/10.1016/j.aos.2017.07.001
  42. Maranges, H.M., & Strickhouser, J.E. (2022). Does ecology or character matter? The contributions of childhood unpredictability, harshness, and temperament to life history strategies in adolescence. Evolutionary Behavioral Sciences, 16(4), 313–329. https:// doi.org/10.1037/ebs0000266
  43. Maranges, H.M., Hasty, C.R., Martinez, J.L., & Maner, J.K. (2022). Adaptive calibration in early development: Brief measures of perceived childhood harshness and unpredictability. Adaptive Human Behavior and Physiology, 8(3), 313–343. https://doi.org/10.1007/s40750-022-00200-z
  44. Martinez, J.L., Hasty, C., Morabito, D., Maranges, H.M., Schmidt, N.B., & Maner, J.K. (2022). Perceptions of childhood unpredictability, delay discounting, risk-taking, and adult externalizing behaviors: A life-history approach. Development and Psychopathology, 34(2), 705–717. https://doi.org/10.1017/s0954579421001607
  45. McDonald, B., & Kanske, P. (2023). Gender differences in empathy, compassion, and prosocial donations, but not theory of mind in a naturalistic social task. Scientific Reports, 13(1), 20748. https://doi.org/10.1038/s41598-023-47747-9
  46. Međedović, J. (2020). Examining the link between religiousness and fitness in a behavioural ecological framework. Journal of Biosocial Science, 52(5), 756–767. https://doi.org/ 10.1017/s0021932019000774
  47. Međedović, J. (2023a). Evolutionary Behavioral Ecology and Psychopathy. Cham: Springer. https://doi.org/10.1007/978-3-031-32886-2
  48. Međedović, J. (2023b). Pace-of-Life Syndrome (POLS). In T.K. Shackelford (Ed.), Encyclopedia of Sexual Psychology and Behavior (pp. 1–5). Cham: Springer. https://doi.org/ 10.1007/978-3-031-08956-5_1677-1
  49. Mendle, J., Turkheimer, E., & Emery, R.E. (2007). Detrimental psychological outcomes associated with early pubertal timing in adolescent girls. Developmental Review, 27(2), 151–171. https://doi.org/10.1016/j.dr.2006.11.001
  50. Minkov, M. (2014). The K factor, societal hypometropia, and national values: A study of 71 nations. Personality and Individual Differences, 66, 153–159. https://doi.org/10.1016/j.paid.2014.03.021
  51. Olderbak, S., Gladden, P., Wolf, P.S.A., & Figueredo, A.J. (2014). Comparison of life history strategy measures. Personality and Individual Differences, 58, 82–88. https://doi.org/ 10.1016/j.paid.2013.10.012
  52. Reynolds-Salmon, R., Samms-Vaughan, M., Coore-Desai, C., Reece, J., & Pellington, S. (2024). Does household size matter? Crowding and its effects on child development. Psychology, Health & Medicine, 29(6), 1165–1178. https://doi.org/10.1080/13548506.2024.2326867
  53. Richardson, G.B., Bates, D., Ross, A., Liu, H., & Boutwell, B.B. (2024). Is reproductive development adaptively calibrated to early experience? Evidence from a national sample of females. Developmental Psychology, 60(2), 306–321. https://doi.org/10.1037/dev0001681
  54. Richardson, G.B., Sanning, B.K., Lai, M.H.C., Copping, L.T., Hardesty, P.H., & Kruger, D.J. (2017). On the psychometric study of human life history strategies. Evolutionary Psychology, 15(1), 1–24. https://doi.org/10.1177/1474704916666840
  55. Rusalov, V. (2018). Functional systems theory and the activity-specific approach in psychological taxonomies. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1744), 20170166. https://doi.org/10.1098/rstb.2017.0166
  56. Sefcek, J.A., & Figueredo, A.J. (2010). A life-history model of human fitness indicators. Biodemography and Social Biology, 56(1), 42–66. https://doi.org/10.1080/ 19485561003709214
  57. Sheridan, M.A., & McLaughlin, K.A. (2014). Dimensions of early experience and neural development: Deprivation and threat. Trends in Cognitive Sciences, 18(11), 580–585. https://doi.org/10.1016/j.tics.2014.09.001
  58. Sirganci, G., Uyumaz, G., & Yandi, A. (2020). Measurement invariance testing with alignment method: Many groups comparison. International Journal of Assessment Tools in Education, 7(4), 657–673. https://doi.org/10.21449/ijate.714218
  59. Skirbekk, V. (2022). Decline and Prosper! Changing Global Birth Rates and the Advantages of Fewer Children. Cham: Springer. https://doi.org/10.1007/978-3-030-91611-4
  60. Sodini, S.M., Kemper, K.E., Wray, N.R., & Trzaskowski, M. (2018). Comparison of genotypic and phenotypic correlations: Cheverud’s conjecture in humans. Genetics, 209(3), 941–948. https://doi.org/10.1534/genetics.117.300630
  61. Solari, C.D., & Mare, R.D. (2012). Housing crowding effects on children’s wellbeing. Social Science Research, 41(2), 464–476. https://doi.org/10.1016/j.ssresearch.2011.09.012
  62. Stearns, S.C., & Rodrigues, A.M.M. (2020). On the use of “life history theory” in evolutionary psychology. Evolution and Human Behavior, 41(6), 474–485. https://doi.org/10.1016/j.evolhumbehav.2020.02.001
  63. Stott, I., Salguero-Gómez, R., Jones, O.R., Ezard, T.H.G., Gamelon, M., Lachish, S., Lebreton, J.-D., Simmonds, E.G., Gaillard, J.-M., & Hodgson, D.J. (2024). Life histories are not just fast or slow. Trends in Ecology & Evolution, 39(9), 830–840. https://doi.org/10.1016/j.tree.2024.06.001
  64. Szepsenwol, O., & Simpson, J.A. (2019). Attachment within life history theory: an evolutionary perspective on individual differences in attachment. Current Opinion in Psychology, 25, 65–70. https://doi.org/10.1016/j.copsyc.2018.03.005
  65. Takesian, A.E., & Hensch, T.K. (2013). Balancing plasticity/stability across brain development. Progress in Brain Research, 207, 3–34. https://doi.org/10.1016/b978-0-444-63327-9.00001-1
  66. Tarka, M., Guenther, A., Niemelä, P.T., Nakagawa, S., & Noble, D.W.A. (2018). Sex differences in life history, behavior, and physiology along a slow-fast continuum: A meta-analysis. Behavioral Ecology and Sociobiology, 72(8), 132. https://doi.org/10.1007/s00265-018-2534-2
  67. Trofimova, I. (2021). Functional constructivism approach to multilevel nature of bio-behavioral diversity. Frontiers in Psychiatry, 12, 641286. https://doi.org/10.3389/fpsyt.2021.641286
  68. Volk, A.A. (2023). Historical and hunter-gatherer perspectives on fast-slow life history strategies. Evolution and Human Behavior, 44(2), 99–109. https://doi.org/10.1016/j.evolhumbehav.2023.02.006
  69. Volk, A.A. (2025). Pumping the brakes on psychosocial acceleration theory: Revisiting its underlying assumptions. Evolution and Human Behavior, 46(1), 106657. https://doi.org/ 10.1016/j.evolhumbehav.2025.106657
  70. Webster, G.D., Graber, J.A., Gesselman, A.N., Crosier, B.S., & Schember, T.O. (2014). A life history theory of father absence and menarche: A meta-analysis. Evolutionary Psychology, 12(2), 273–294. https://doi.org/10.1177/147470491401200202
  71. Welling, L.L.M., & Shackelford, T.K. (Eds.). (2019). The Oxford Handbook of Evolutionary Psychology and Behavioral Endocrinology. Oxford: Oxford University Press. https://doi.org/10.1093/oxfordhb/9780190649739.001.0001
  72. Wingfield J. C. (2017). The challenge hypothesis: Where it began and relevance to humans. Hormones and behavior, 92, 9–12. https://doi.org/10.1016/j.yhbeh.2016.11.008
  73. Wu, J., Guo, Z., Gao, X., & Kou, Y. (2020). The relations between early-life stress and risk, time, and prosocial preferences in adulthood: A meta-analytic review. Evolution and Human Behavior, 41(6), 557–572. https://doi.org/10.1016/j.evolhumbehav.2020.09.001
  74. Xu, Y., Norton, S., & Rahman, Q. (2018). Early life conditions, reproductive and sexuality-related life history outcomes among human males: A systematic review and meta-analysis. Evolution and Human Behavior, 39(1), 40–51. https://doi.org/10.1016/j.evolhumbehav.2017.08.005
  75. Yang, A.T., Lu, H.J., & Chang, L. (2023). Environmental harshness and unpredictability, parenting, and offspring life history. Evolutionary Psychological Science, 9(4), 451–462. https://doi.org/10.1007/s40806-023-00375-y
  76. Young, E.S., Frankenhuis, W.E., & Ellis, B.J. (2020). Theory and measurement of environmental unpredictability. Evolution and Human Behavior, 41(6), 550–556. https://doi.org/ 10.1016/j.evolhumbehav.2020.08.006
  77. Young, E.S., Griskevicius, V., Simpson, J.A., Waters, T.E.A., & Mittal, C. (2018). Can an unpredictable childhood environment enhance working memory? Testing the sensitized-specialization hypothesis. Journal of Personality and Social Psychology, 114(6), 891–908. https://doi.org/10.1037/pspi0000124

补充文件

附件文件
动作
1. JATS XML
下载

Согласие на обработку персональных данных с помощью сервиса «Яндекс.Метрика»

1. Я (далее – «Пользователь» или «Субъект персональных данных»), осуществляя использование сайта https://journals.rcsi.science/ (далее – «Сайт»), подтверждая свою полную дееспособность даю согласие на обработку персональных данных с использованием средств автоматизации Оператору - федеральному государственному бюджетному учреждению «Российский центр научной информации» (РЦНИ), далее – «Оператор», расположенному по адресу: 119991, г. Москва, Ленинский просп., д.32А, со следующими условиями.

2. Категории обрабатываемых данных: файлы «cookies» (куки-файлы). Файлы «cookie» – это небольшой текстовый файл, который веб-сервер может хранить в браузере Пользователя. Данные файлы веб-сервер загружает на устройство Пользователя при посещении им Сайта. При каждом следующем посещении Пользователем Сайта «cookie» файлы отправляются на Сайт Оператора. Данные файлы позволяют Сайту распознавать устройство Пользователя. Содержимое такого файла может как относиться, так и не относиться к персональным данным, в зависимости от того, содержит ли такой файл персональные данные или содержит обезличенные технические данные.

3. Цель обработки персональных данных: анализ пользовательской активности с помощью сервиса «Яндекс.Метрика».

4. Категории субъектов персональных данных: все Пользователи Сайта, которые дали согласие на обработку файлов «cookie».

5. Способы обработки: сбор, запись, систематизация, накопление, хранение, уточнение (обновление, изменение), извлечение, использование, передача (доступ, предоставление), блокирование, удаление, уничтожение персональных данных.

6. Срок обработки и хранения: до получения от Субъекта персональных данных требования о прекращении обработки/отзыва согласия.

7. Способ отзыва: заявление об отзыве в письменном виде путём его направления на адрес электронной почты Оператора: info@rcsi.science или путем письменного обращения по юридическому адресу: 119991, г. Москва, Ленинский просп., д.32А

8. Субъект персональных данных вправе запретить своему оборудованию прием этих данных или ограничить прием этих данных. При отказе от получения таких данных или при ограничении приема данных некоторые функции Сайта могут работать некорректно. Субъект персональных данных обязуется сам настроить свое оборудование таким способом, чтобы оно обеспечивало адекватный его желаниям режим работы и уровень защиты данных файлов «cookie», Оператор не предоставляет технологических и правовых консультаций на темы подобного характера.

9. Порядок уничтожения персональных данных при достижении цели их обработки или при наступлении иных законных оснований определяется Оператором в соответствии с законодательством Российской Федерации.

10. Я согласен/согласна квалифицировать в качестве своей простой электронной подписи под настоящим Согласием и под Политикой обработки персональных данных выполнение мною следующего действия на сайте: https://journals.rcsi.science/ нажатие мною на интерфейсе с текстом: «Сайт использует сервис «Яндекс.Метрика» (который использует файлы «cookie») на элемент с текстом «Принять и продолжить».