Pré-publicação
Artigos

Una lectura representacional de los pilares de la vision estadistica: hacia un análisis perspectivista en biología poblacional

PDF (Español (España))
  • Cristián Novelli,
  • Tiago Rama
Cristián Novelli
Subunidad de Lógica y Metodología, Unidad Académica Instituto de Filosofía, Facultad de Humanidades y Ciencias de la Educación, Universidad de la República, Montevideo, Uruguay.
Tiago Rama
Subunidad de Filosofía e Historia de la Ciencia, Unidad Académica Instituto de Filosofía, Facultad de Humanidades y Ciencias de la Educación, Universidad de la República, Montevideo, Uruguay.
DOI: https://doi.org/10.36446/af.e1282

Publicado 2026-06-24

Creative Commons License

Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial 4.0 International License.

Resumo

Dentro del ámbito de la teoría evolutiva, las posturas causalista y estadística postulan diferentes formas de entender los conceptos y parámetros que los modelos poblacionales de la Síntesis Moderna involucran. En especial, la discusión se centra en gran parte sobre si la selección natural y la deriva deben entenderse como procesos causales o como parámetros estadísticos de los modelos. Este trabajo propone una lectura representacional de los compromisos centrales establecidos por una de estas posturas: los cuatro “pilares” de la visión estadística (Walsh et al., 2017). Para esto se realiza un análisis de los mismos a partir de las herramientas conceptuales del acercamiento de Van Fraassen (2008) en cuanto a la representación científica, entendiendo los pilares de la visión estadística como consecuencias del carácter representacional de los modelos poblacionales. A la hora de establecer cada uno de los pilares, enfatizamos la relevancia puesta en el uso de los modelos para ciertos objetivos científicos, así como en las características perspectivistas de los modelos poblacionales. Esto nos permite contrarrestar ciertas críticas e interpretaciones que la visión estadística ha recibido; en particular, argumentamos que es incorrecto asumir que la visión estadística establece que la genética poblacional sea “simplemente” matemática.

PDF (Español (España))

Referências

  1. Abrams, M. (2007). How do natural selection and random drift interact? Philosophy of Science, 74(5), 666-679. https://doi.org/10.1086/525612
  2. Abrams, M. (2012). Measured, modeled, and causal conceptions of fitness. Frontiers in Genetics, 3. https://doi.org/10.3389/fgene.2012.00196
  3. Ariew, A. (2003). Ernst Mayr’s «ultimate/proximate» distinction reconsidered and reconstructed. Biology & Philosophy, 18(4), 553-565. https://doi.org/10.1023/A:1025565119032
  4. Ariew, A., & Ernst, Z. (2009). What fitness can’t be. Erkenntnis, 71(3), 289-301. https://doi.org/10.1007/s10670-009-9183-9
  5. Ariew, A., & Lewontin, R. C. (2004). The confusions of fitness. The British Journal for the Philosophy of Science, 55(2), 347-363. https://doi.org/10.1093/bjps/55.2.347
  6. Ariew, A., Rice, C., & Rohwer, Y. (2015). Autonomous-statistical explanations and natural selection. The British Journal for the Philosophy of Science, 66(3), 635-658. https://doi.org/10.1093/bjps/axt054
  7. Baravalle, L., Roffé, A. J., Luque, V. J., & Ginnobili, S. (2025). The value of Price. Biological Theory, 20(1), 12-24. https://doi.org/10.1007/s13752-024-00482-4
  8. Beatty, J. (1998). Fitness: Theoretical contexts. En E. Fox Keller & E. A. Lloyd (Eds.), Keywords in evolutionary biology (pp. 115-119). Harvard University Press.
  9. Bowler, P. J. (2020). Evolution: The history of an idea. University of California Press.
  10. Boyd, R., & Richerson, P. J. (1985). Culture and the evolutionary process. University of Chicago Press. https://press.uchicago.edu/ucp/books/book/chicago/C/bo5970597.html
  11. Brandon, R. N., & Ramsey, G. (2007). What’s wrong with the emergentist statistical interpretation of natural selection and random drift? En D. L. Hull & M. Ruse (Eds.), The Cambridge companion to the philosophy of biology (1.a ed., pp. 66-84). Cambridge University Press. https://doi.org/10.1017/CCOL9780521851282.004
  12. Bueno, O., & French, S. (2018). Applying mathematics: Immersion, inference, interpretation (1.a ed.). Oxford University Press.
  13. Day, T., & Bonduriansky, R. (2011). A unified approach to the evolutionary consequences of genetic and nongenetic inheritance. The American Naturalist, 178(2), 145-286 . https://doi.org/10.1086/660911
  14. de Regt, H. W. (2017). Understanding scientific understanding. Oxford University Press. https://doi.org/10.1093/oso/9780190652913.001.0001
  15. Edelaar, P., Otsuka, J., & Luque, V. J. (2023). A generalised approach to the study and understanding of adaptive evolution. Biological Reviews, 98(1), 352-375. https://doi.org/10.1111/brv.12910
  16. Fisher, R. A. (1930). The genetical theory of natural selection. Clarendon Press. http://archive.org/details/geneticaltheoryo031631mbp
  17. Fisher, R. A. (1953). Croonian lecture - Population genetics. Proceedings of the Royal Society of London. Series B - Biological Sciences, 141(905), 510-523. https://doi.org/10.1098/rspb.1953.0058
  18. Fogarty, L., & Wade, M. J. (2022). Niche construction in quantitative traits: Heritability and response to selection. Proceedings of the Royal Society B: Biological Sciences, 289(1976), 20220401. https://doi.org/10.1098/rspb.2022.0401
  19. Giere, R. N. (2006). Scientific perspectivism. University of Chicago Press.
  20. Ginnobili, S. (2016). Missing concepts in natural selection theory reconstructions. History and Philosophy of the Life Sciences, 38(3), 8. https://doi.org/10.1007/s40656-016-0109-y
  21. Godfrey-Smith, P. (2009). Darwinian populations and natural selection. Oxford University Press. https://doi.org/10.1093/acprof:osobl/9780199552047.001.0001
  22. Gould, E., Fraser, H. S., Parker, T. H., Nakagawa, S., Griffith, S. C., Vesk, P. A., Fidler, F., Hamilton, D. G., Abbey-Lee, R. N., Abbott, J. K., Aguirre, L. A., Alcaraz, C., Aloni, I., Altschul, D., Arekar, K., Atkins, J. W., Atkinson, J., Baker, C. M., Barrett, M., … Zitomer, R. A. (2025). Same data, different analysts: Variation in effect sizes due to analytical decisions in ecology and evolutionary biology. BMC Biology, 23(1), 35. https://doi.org/10.1186/s12915-024-02101-x
  23. Grene, M. (1961). Statistics and selection. The British Journal for the Philosophy of Science, 12(45), 25-42. https://doi.org/10.1093/bjps/XII.45.25
  24. Hacking, I. (2014). Why is there a philosophy of mathematics at all? Cambridge University Press. https://doi.org/10.1017/CBO9781107279346
  25. Hamilton, W. D. (1964). The genetical evolution of social behaviour. I. Journal of Theoretical Biology, 7(1), 1-16. https://doi.org/10.1016/0022-5193(64)90038-4
  26. Helanterä, H., & Uller, T. (2010). The Price equation and extended inheritance. Philosophy and Theory in Biology, 2(1), e101. https://doi.org/10.3998/ptb.6959004.0002.001
  27. Jeler, C. (2026). Environmental homogeneity, selective paths, and the individuation of selection processes. Erkenntnis 91, 2221–2242. https://doi.org/10.1007/s10670-025-00989-7
  28. Knudsen, T. (2004). General selection theory and economic evolution: The Price equation and the replicator/interactor distinction. Journal of Economic Methodology, 11(2), 147-173. https://doi.org/10.1080/13501780410001694109
  29. Laland, K. N., Uller, T., Feldman, M. W., Sterelny, K., Müller, G. B., Moczek, A., Jablonka, E., & Odling-Smee, J. (2015). The extended evolutionary synthesis: Its structure, assumptions and predictions. Proceedings of the Royal Society B: Biological Sciences, 282(1813), 20151019. https://doi.org/10.1098/rspb.2015.1019
  30. Levins, R. (1966). The strategy of model building in population biology. American Scientist, 54(4), 421-431. https://www.jstor.org/stable/27836590
  31. Lewens, T. (2019). The extended evolutionary synthesis: What is the debate about, and what might success for the extenders look like? Biological Journal of the Linnean Society, 127(4), 707-721. https://doi.org/10.1093/biolinnean/blz064
  32. Luque, V. J. (2016a). The force interpretation of evolutionary theory: Scope and limits. [Tesis de doctorado, Universitat de València]. https://core.ac.uk/reader/75989390
  33. Luque, V. J. (2016b). The principle of stasis: Why drift is not a zero-cause law. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 57, 71-79. https://doi.org/10.1016/j.shpsc.2016.04.001
  34. Luque, V. J. (2017). One equation to rule them all: A philosophical analysis of the Price equation. Biology & Philosophy, 32(1), 97-125. https://doi.org/10.1007/s10539-016-9538-y
  35. Massimi, M. (2022). Perspectival realism (1.a ed.). Oxford University Press. https://doi.org/10.1093/oso/9780197555620.001.0001
  36. Massimi, M., & McCoy, C. D. (Eds.) (2019). Understanding perspectivism: Scientific challenges and methodological prospects. Taylor & Francis. https://doi.org/10.4324/9781315145198
  37. Matthen, M. (2010). What is drift? A Response to Millstein, Skipper, and Dietrich. Philosophy and Theory in Biology, 2(2), e102. https://doi.org/10.3998/ptb.6959004.0002.002
  38. Matthen, M., & Ariew, A. (2002). Two ways of thinking about fitness and natural selection. Journal of Philosophy, 99(2), 55-83. https://doi.org/10.2307/3655552
  39. Matthen, M., & Ariew, A. (2009). Selection and causation. Philosophy of Science, 76(2), 201-224. https://doi.org/10.1086/648102
  40. Millstein, R. L. (2006). Natural selection as a population-level causal process. The British Journal for the Philosophy of Science, 57(4), 627-653. https://doi.org/10.1093/bjps/axl025
  41. Millstein, R. L., Skipper Jr., R. A., & Dietrich, M. R. (2009). (Mis)interpreting mathematical models: Drift as a physical process. Philosophy and Theory in Biology, 1(2), e002. https://doi.org/10.3998/ptb.6959004.0001.002
  42. Morrison, M. (2015). Reconstructing reality: Models, mathematics, and simulations. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199380275.001.0001
  43. Nicholson, D. J. (2025). Population thinking and the uniqueness of biological entities. Acta Biotheoretica, 73(2), 8. https://doi.org/10.1007/s10441-025-09498-0
  44. Okasha, S. (2006). Evolution and the levels of selection. Clarendon Press. https://doi.org/10.1093/acprof:oso/9780199267972.001.0001
  45. Otsuka, J. (2015). Using causal models to integrate proximate and ultimate causation. Biology & Philosophy, 30(1), 19-37. https://doi.org/10.1007/s10539-014-9448-9
  46. Otsuka, J. (2016). A critical review of the statisticalist debate. Biology & Philosophy, 31(4), 459-482. https://doi.org/10.1007/s10539-016-9528-0
  47. Otsuka, J. (2019). The role of mathematics in evolutionary theory. Cambridge University Press. https://doi.org/10.1017/9781108672115
  48. Pence, C. H. (2017). Is genetic drift a force? Synthese, 194(6), 1967-1988. https://doi.org/10.1007/s11229-016-1031-2
  49. Pence, C. H. (2021). The causal structure of natural selection (1.a ed.). Cambridge University Press. https://doi.org/10.1017/9781108680691
  50. Pence, C. H., & Ramsey, G. (2015). Is organismic fitness at the basis of evolutionary theory? Philosophy of Science, 82(5), 1081-1091. https://doi.org/10.1086/683442
  51. Potochnik, A. (2017). Idealization and the aims of science. University of Chicago Press.
  52. Price, G. R. (1970). Selection and covariance. Nature, 227(5257), 520-521. https://doi.org/10.1038/227520a0
  53. Queller, D. C. (2017). Fundamental theorems of evolution. The American Naturalist, 189(4), 345-353. https://doi.org/10.1086/690937
  54. Rama, T. (2023). Evolutionary causation and teleosemantics. En J. M. Viejo & M. Sanjuán (Eds.), Life and mind (Interdisciplinary Evolution Research, vol. 8, pp. 301-329). Springer International Publishing. https://doi.org/10.1007/978-3-031-30304-3_14
  55. Rama, T. (2024). The historical transformation of individual concepts into populational ones: An explanatory shift in the gestation of the modern synthesis. History and Philosophy of the Life Sciences, 46(4), 35. https://doi.org/10.1007/s40656-024-00638-2
  56. Rama, T. (2025). Reciprocal causation and statistical reciprocity. Acta Biotheoretica, 73(4), 15. https://doi.org/10.1007/s10441-025-09506-3
  57. Rama, T. (2026). The problem of models: Can quantitative evolutionary biology also call for an EES? Evolutionary Biology. https://doi.org/10.1007/s11692-026-09672-3
  58. Ramsey, G. (2016). The causal structure of evolutionary theory. Australasian Journal of Philosophy, 94(3), 421-434. https://doi.org/10.1080/00048402.2015.1111398
  59. Reisman, K., & Forber, P. (2005). Manipulation and the causes of evolution. Philosophy of Science, 72(5), 1113-1123. https://doi.org/10.1086/508120
  60. Rosenberg, A. (2008). Darwinian reductionism: Or, how to stop worrying and love molecular biology. University of Chicago Press.
  61. Rosenberg, A., & Bouchard, F. (2005). Matthen and Ariew’s obituary for fitness: Reports of its death have been greatly exaggerated. Biology & Philosophy, 20(2-3), 343-353. https://doi.org/10.1007/s10539-005-2560-0
  62. Sober, E. (1980). Evolution, population thinking, and essentialism. Philosophy of Science, 47(3), 350-383. https://doi.org/10.1086/288942
  63. Sober, E. (1984). The nature of selection: Evolutionary theory in philosophical focus. University of Chicago Press.
  64. Steiner, M. (1998). The applicability of mathematics as a philosophical problem. Harvard University Press.
  65. Stephens, C. (2004). Selection, drift, and the “forces” of evolution. Philosophy of Science, 71(4), 550-570. https://doi.org/10.1086/423751
  66. Suárez, M. (2024). Inference and representation: A study in modeling science. The University of Chicago Press. https://doi.org/10.7208/chicago/9780226830032.001.0001
  67. van Fraassen, B. C. (2008). Scientific representation: Paradoxes of perspective. Clarendon Press. https://doi.org/10.1093/acprof:oso/978 0199278220.001.0001
  68. Wade, M. J., & Sultan, S. E. (2023). Niche construction and the environmental term of the Price equation: How natural selection changes when organisms alter their environments. Evolution & Development, 25(6), 451-469. https://doi.org/10.1111/ede.12452
  69. Walsh, D. M. (2007). The pomp of superfluous causes: The interpretation of evolutionary theory. Philosophy of Science, 74(3), 281-303. https://doi.org/10.1086/520777
  70. Walsh, D. M. (2013). Descriptions and models: Some responses to Abrams. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 44(3), 302-308. https://doi.org/10.1016/j.shpsc.2013.06.004
  71. Walsh, D. M. (2019). The paradox of population thinking: First order causes and higher order effects. En T. Uller & K. N. Lala (Eds.), Evolutionary causation: Biological and Philosophical Reflections (pp. 227-246). The MIT Press. https://doi.org/10.7551/mitpress/11693.003.0012
  72. Walsh, D. M., Ariew, A., & Matthen, M. (2017). Four pillars of statisticalism. Philosophy, Theory, and Practice in Biology, 9(1), 1. https://doi.org/10.3998/ptb.6959004.0009.001
  73. Walsh, D. M., Lewens, T., & Ariew, A. (2002). The trials of life: Natural selection and random drift. Philosophy of Science, 69(3), 452-473. https://doi.org/10.1086/342454
  74. Walsh, D. M., & Rupik, G. (2023). The agential perspective: Countermapping the modern synthesis. Evolution & Development, 25(6), 335-352. https://doi.org/10.1111/ede.12448
  75. Weisberg, M. (2007). Forty years of ‘The Strategy’: Levins on model building and idealization. Biology & Philosophy, 21(5), 623-645. https://doi.org/10.1007/s10539-006-9051-9
  76. Wimsatt, W. C. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality. Harvard University Press.
  77. Winther, R. G. (2020). When maps become the world. University of Chicago Press.