"Must We All Die?": Alaska's Enduring Struggle with Tuberculosis, by Robert Fortuine
Bibliographic record
Abstract
Robert Fortuine (pronounced Four-TYNE) is Alaska's pre-eminent medical historian.As we expected, this factfilled book is thoroughly researched and meticulously documented.His preface begins with an account of an xray survey in a remote village early in 1946, when a distraught father pleaded, "Five of my children die this way -I don't want my other kids to go.Must we all die of the TB?"For the educated layperson, anthropologist, or historian, Fortuine's introductory chapter provides necessary background concerning the medical aspects and history of tuberculosis (TB), a disease that is carried by one-third of the world's population, killing about 1.8 million people each year, and still increasing in incidence globally.During the Russian occupation of Alaska (1741 -1867), TB was readily transmitted from infected Russians to the aboriginal people.The Native people lived in relative poverty under crowded and unhygienic conditions, so that the almost unprecedented TB epidemic spread like wildfire across Alaska, affecting people of all ages.From 1926 to 1930, the TB death rate for Alaska Natives was 655 per 100 000, compared to 42 per 100 000 for whites.In southeastern Alaska, females aged 20 to 29, in their prime childbearing years, had the horrific mortality
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".