Bibliographic record
Abstract
Abstract This chapter sets out to explore personal memory of living in São Paulo, Brazil during the ‘Spanish’ Flu. The city was badly hit in the last quarter of 1918 by the second and most deadly wave of the influenza pandemic, when it arrived in Brazil and practically spread throughout the entire national territory. The primary source examined is a testimony, recorded in the 1980s, of Dona Rosa Fazio Fávero, who at the time of the pandemic was thirteen years old. She noted how, despite the medical measures taken by her middle-class parents to keep the family safe, one of her sisters was infected with flu, albeit in a mild form. She recalled how her parents showed sympathy to members of the neighbourhood, offering shelter and food to those most in need. From Dona Rosa’s testimony, which highlights the forms of solidarity that allowed the city to overcome the great health crisis, it is evident that this experience was remembered as a defining moment in her life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 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; both teacher heads agree on what is shown here.
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".