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Record W2926003524 · doi:10.1163/15734218-12341412

Cumin, Capsules, and Colonialism

2018· article· en· W2926003524 on OpenAlexaff
Shobna Nijhawan

Bibliographic record

VenueAsian Medicine · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsYork University
Fundersnot available
KeywordsColonialismIndigenousHindiPoliticsInstitutionalisationNationalismMedicineTraditional medicineHistorySocial scienceSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract The institutionalization of Western allopathic medicine in colonial India had significant implications for the cultural politics of the early twentieth century. The introduction of vaccinations, the establishment of hospitals and dispensaries, scientific discourses on hygiene, bacteriology, and nutrition, the emergence of obstetrics and gynecology as medical disciplines, and the commercialization of medicine—to name but a few aspects of the institutionalization or elements leading thereto—were all topics that also concerned the Hindi literary sphere. This essay investigates how the Hindi literary public tackled the colonial state’s promotion of allopathy and modern sciences while, within the same discourse, it (re)discovered, systemized, and modernized indigenous medical knowledge traditions—most notably Ayurveda but also homespun remedies and folk medicine—for the prevention, treatment, and cure of disease. Prose fiction and prose essays, alongside advertisements in Hindi periodicals, testify to a range of opinions on what constituted a “healthy” blend of diverse “Eastern” and diverse “Western” medical traditions. This essay argues that the Hindi discourse on medicine and colonial modernity was steered by gendered nationalist politics, modern Western sciences, and commercial interests in maintaining a healthy body and working toward a healthy nation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.022
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.027
GPT teacher head0.230
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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