Bibliographic record
Abstract
Volume 9: Florence Nightingale on Health in India is the first of two volumes reporting Nightingale’s forty years of work to improve public health in India. It begins with her work to establish the Royal Commission on the Sanitary State of the Army in India, for which she drafted questionnaires, analyzed returns, and did much of the final writing, going on to promote the implementation of its recommendations. In this volume a gradual shift of attention can be seen from the health of the army to that of the civilian population. Famine and epidemics were frequent and closely interrelated occurrences. To combat them, Nightingale recommended a comprehensive set of sanitary measures, and educational and legal reforms, to be overseen by a public health agency. Skilful in implementing the expertise, influence, and power of others, she worked with her impressive network of well-placed collaborators, having them send her information and meet with her back in London. The volume includes Nightingale’s work on the royal commission itself, related correspondence, numerous published pamphlets, articles and letters to the editor, and correspondence with her growing network of viceroys, governors of presidencies, and public health experts. Working with British collaborators, she began this work; over time Nightingale increased her contact with Indian nationals and promoted their work and associations. Currently, Volumes 1 to 11 are available in e-book version by subscription or from university and college libraries through the following vendors: Canadian Electronic Library, Ebrary, MyiLibrary, and Netlibrary.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.057 | 0.018 |
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".