13 research outputs found

    Darwin's “Natural Science of Babies”

    No full text
    In 1877, the newly founded British journal Mind published two papers on child development. The earlier, by Hippolyte Taine, prompted the second article: an account of his own son's development by the naturalist Charles Darwin. In its turn, Darwin's paper, “A Biographical Sketch of an Infant,” influenced others. Diary studies similar to Taine's and Darwin's appeared in Mind from 1878. In addition, the medical profession started to consider normal child language acquisition as a comparison for the abnormal. Shortly before his death in 1882, Darwin continued with his theme, setting out a series of proposals for a program of research on child development with suggested methodology and interpretations. Darwin, whose interest in infants and the developing mind predated his 1877 paper by at least 40 years, sought to take the subject out of the nursery and into the scientific domain. The empirical study of the young child's developing mental faculties was a source of evidence with important implications for his general evolutionary theory. The social status of children in England was the subject of considerable discussion around the time Darwin's 1877 paper appeared. Evolutionary theory was still relatively new and fiercely debated, and an unprecedented level of interest was shown by the popular press in advance of the publication. This article considers the events surrounding the publication of Darwin's article in Mind, the notebook of observations on Darwin's children (1839-1856) that served as its basis, and the research that followed publication of “Biographical Sketch.” We discuss the impact this article, one of the first infant psychology studies in English, made on the scientific community in Britain in the latter half of the nineteenth century

    Démarche statistique pour la sélection des indicateurs par Random Forests pour la surveillance de la qualité des sols

    No full text
    The volume of data, and the large number of biological variables to be tested (one hundred), require analytical techniques, such as Random Forests, which can overcome the problem of multi-colinearity for the selection of indicators, sensitive to various factors. Random Forests methodology is appropriate for the selection of the most discriminant variables. So, we searched for the best way to select them, by bringing together all biological variables, representing the Microflora and Fauna. This approach focuses on impact indicators from the Bio2 program, indicators of flora and indicators of accumulation (snails) were not included. This work has been implemented on the three factors of discrimination : land use, metallic contamination levels and organic contamination levels. We grouped the most discriminating variables from each RF analysis. Linear discriminant analysis was then implemented for each factor, in order to develop a predictive model
    corecore