Marginal anthropology? Rethinking Maria Czaplicka and the development of British anthropology from a material history perspective
Bibliographic record
Abstract
This thesis explores the history of British anthropology at the start of the twentieth century through a biographical focus on Maria Antonina Czaplicka (1884-1921). The title calls into question the marginalisation of people and processes in the history of anthropology that do not explicitly contribute to the dominant lineage of British social anthropology and offers to add depth and nuance to the narrative through analysis stemming from material sources. I use Czaplicka as a case study to demonstrate how close attention to a seemingly marginal person with an incomplete and scattered archival record, can help formulate a clearer picture of what anthropology was and what it can thus become. My research contributes to the understanding and appreciation of women’s involvement in anthropology, calls into question national borders of the discipline at this point in time, highlights the networks that nurtured it, and demonstrates the potential that museum collections have for an enriched understanding of the history of anthropology. I propose that history of anthropology is better understood through a planar approach that allows multiple parallel developments to exist together rather than envisaging a linear evolution towards a single definition of social anthropology. The project lays the groundwork for further research into the role that museums can have for understanding anthropological legacy and the possibilities they may have in creating fresh understandings of the contemporary world.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.059 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".