Bibliographic record
Abstract
Published in 1998, Ladies in the Laboratory provided a systematic survey and comparison of the work of 19th-century American and British women in scientific research. A companion volume, published in 2004, focused on women scientists from Western Europe. In this third volume, author Mary R.S. Creese expands her scope to include the contributions of 19th- and early 20th-century women of South Africa, Australia, New Zealand, and Canada. The women whose lives and work are discussed here range from natural history collectors and scientific illustrators of the early and mid years of the 19th century to the first generation of graduates of the new colonial colleges and universities. Rarely acknowledged in publications of the British and European specialists, the contributions of these women nonetheless formed a significant part of the natural history information about extensive, previously unknown regions and their products. Rather than a biographical dictionary or a collection of self-contained essays on individuals from many time periods, Ladies in the Laboratory III is a connected narrative tied into the wider framework of 19th-century science and education. A well-organized blend of individual life stories and quantitative information, this volume is for everyone interested in the story of women's participation in 19th century science. The stories of these women make for fascinating reading and serve as a valuable source for the student of women's and colonial history.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.095 | 0.024 |
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".