Bibliographic record
Abstract
Franz Boas, born in Minden, Westphalia, is commonly regarded as the most influential figure of American anthropology in the first third of the twentieth century. Raised in an assimilated Jewish family, which had strong sympathies for the liberal ideals of the revolution of 1848, Boas studied natural sciences and mathematics at the universities of Heidelberg, Bonn, and Kiel, graduating in 1881. In a complex intellectual “odyssey” he abandoned his materialistic Weltanschauung and, under the influence of neo‐Kantianism, shifted his attention from the field of physics to Fechnerian psychophysics to Ratzel's anthropogeography, and finally, several years after graduating from university, to ethnology (Stocking 1982: 133–60). In 1883–4 he spent a year among the Inuit of Baffinland to examine the influence of the natural environment on the life of the people. Upon his return to Germany Boas published the results of his first fieldwork, obtained the docentship for geography at the University of Berlin, intensified his relationship with the leading German physical anthropologist, pathologist, and liberal politician R. Virchow, and worked as an assistant of A. Bastian at the Royal Ethnographical Museum at Berlin. Fascinated by the museum's collection of North Pacific Coast culture, Boas went to do fieldwork in British Columbia in 1886. The culture of the Native Americans of the Northwest Coast was to remain at the center of Boas's ethnographic research throughout his life. Returning to New York in 1887, Boas accepted the position as an assistant editor of the journal Science and, for political, professional, and personal reasons, decided to settle in the New World. From 1889 to 1892 he taught anthropology at Clark University, supervising the first American PhD in anthropology. From 1892 to 1894 he worked as an anthropologist at the World's Columbian Exposition at Chicago. While serving as a curator of the American Museum of Natural History (1896–1905) Boas organized the famous Jesup North Pacific Expedition, which set out to study the historical relationships between Asian and North American peoples. In 1896 he became a lecturer of physical anthropology and in 1899 was appointed the first full professor of anthropology at Columbia University, a post he held until his retirement in 1936–7.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.012 |
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".