Bibliographic record
Abstract
Florence Nightingale’s Suggestions for Thought has intrigued readers from feminist-philosopher J.S. Mill (who used it in his The Subjection of Women ) to the latest generation of women’s activists. Although selections from this long work have been published, Lynn McDonald is the first editor to work through the numerous surviving drafts of Nightingale’s writing and present it as a complete volume. Suggestions for Thought contains two early attempted novels, draft sermons, and a lengthy fictional dialogue featuring St. Ignatius, founder of the Jesuits, the American evangelical Jacob Abbott, and British agnostic Harriet Martineau (with cameo appearances by Protestant reformer John Calvin and the poet Shelley) all against an unnamed “M.S.” The most famous section of Suggestions for Thought is the essay Cassandra, famous as a rant against the family for stifling womens aspirations. Here the printed text is shown with the original novel draft alongside. McDonald’s introductions to each section provide historical context and Nightingales later views of the work. 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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.037 | 0.014 |
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".