Digital history and the specimen database: Mohamed Haniff (1872–1930) and colonial ethnobotany in the Singapore Herbarium
Bibliographic record
Abstract
With a focus on specimens from 1920s Malaya in the Singapore Herbarium (SING), this paper explores how historians can productively engage with natural science collections databases to study botanical collecting. The database is the most recent iteration of a longer history of information organization in the herbarium. This history, combined with an analysis of the transformation of the herbarium sheet into specimen metadata, informs the development of a critical digital humanities approach to reading a database of historical specimens as a colonial archive. The addition of digital methods to the historian’s toolkit can help ‘cross-contextualize’ the overlapping digital, textual, and material products of natural history to draw together traces of historical figures under-represented in surviving written records. The central case study is the career of Penang-born botanist Mohamed Haniff (1872–1930) and his contributions to ‘Malay village medicine’ (1930), a materia medica compendium co-authored with Singapore Botanic Gardens Director Isaac Henry Burkill (1870–1965). Triangulating between metadata from the specimen database, ‘Malay village medicine’, and herbarium sheets reveals details of Haniff’s collecting itineraries and ethnobotanical encounters with traditional knowledge keepers, like the bomoh (healer) Lebai Ishak. Drawing on geographical metadata and the ethnobotanical compendium, a digital map of Haniff’s encounters with unnamed Malay and Orang Asli bidan (midwives) highlights the limits of these archival excavations. This methodological approach helps foreground local actors’ collecting practices and opens new lines of inquiry into the nature of go-betweens and collaboration in colonial botany.
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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 | 0.000 | 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 | 0.000 | 0.010 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".