Uncertainty and Managing Randomness: The First Documented Cholera Epidemic in Bombay City and Presidency, 1818-1821
Bibliographic record
Abstract
Between 1817 and 1821, the Indian subcontinent was devastated by a series of cholera outbreaks that have subsequently been referred to as the beginning of the First Cholera Pandemic. Although the history of the First Cholera Pandemic has received some scholarly attention, historians tend to overlook the local features of the pandemic in favor of the broader colonial context. In this article, the author contends that the official response to the epidemic in Bombay city and presidency (1818-1821) was initially ameliorative, including recruiting native medical assistants to administer treatment. Such a measure was calculated to cultivate a benevolent image of the colonial government among local inhabitants. Despite considerable nosological and etiological disagreements, members of the Bombay Medical Board characterized cholera as a social disease. Unlike cholera epidemics in the latter half of the nineteenth century, the first cholera epidemic in the Bombay presidency did little to exacerbate antagonism towards the colonial government for two reasons. First, the British power in India was still at its formative stage. Second, both in India and England, cholera was associated with the derangement of bodily humors. On the contrary, the epidemic provided a stimulus to intracommunal discord. Antara tahun 1817 dan 1821, anak benua India dilanda serangkaian wabah kolera yang kemudian disebut sebagai awal dari Pandemi Kolera Pertama. Meskipun sejarah Pandemi Kolera Pertama telah mendapat perhatian ilmiah, para sejarawan cenderung mengabaikan ciri-ciri lokal dari pandemi ini dan lebih memilih konteks kolonial yang lebih luas. Dalam artikel ini, penulis berpendapat bahwa tanggapan resmi terhadap epidemi di kota dan wilayah kepresidenan Bombay (1818-1821) pada awalnya bersifat perbaikan, termasuk merekrut asisten medis pribumi untuk memberikan pengobatan. Tindakan seperti itu diperhitungkan untuk menumbuhkan citra baik pemerintah kolonial di kalangan penduduk setempat. Meskipun ada perbedaan pendapat nosologis dan etiologis, anggota Dewan Medis Bombay menggolongkan kolera sebagai penyakit sosial. Berbeda dengan epidemi kolera pada paruh kedua abad ke-19, epidemi kolera yang pertama pada masa kepresidenan Bombay tidak banyak memperburuk antagonisme terhadap pemerintah kolonial karena dua alasan. Pertama, kekuatan Inggris di India masih dalam tahap pembentukan. Kedua, baik di India maupun Inggris, kolera dikaitkan dengan gangguan humor tubuh. Sebaliknya, epidemi ini memberikan stimulus terhadap perselisihan antar masyarakat.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".