A full catalogue and analysis of Indian painted photographs at Royal Ontario Museum's South Asian photographic collection
Bibliographic record
Abstract
This thesis is based on a photographic collection of Indian painted photographs from the South Asian Photographic collection at the Royal Ontario Museum (ROM). There are fifty-four photographic objects created by various makers and photographers with dates ranging from the 1880's to the 1990's. For the most part the objects are examples of studio portraiture. Most of them are photographic images with applied colour, however, there are some examples of paintings in this group that were executed in the tradition of photographic studio portraiture, but have no evidence of a photosensitive material underneath. The paintings, as well as the painted photographs, employ different media, such as watercolour, gouache and oil paints. The objects I investigated and catalogued fall under three categories: prints made by contact printing, by enlargement, and finally paintings produced using a photograph as a model. Tinting of photographs was a well-known Western tradition in the nineteenth century, while the process that Indian artists developed was a synthesis of their long practiced tradition of miniature painting and the newly developed technology of photography. Finally this thesis unveils the means of production of Indian painted photographs, and tries to find the reason for Indian artists employing opaque medium in their colourings.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.037 | 0.068 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.079 | 0.021 |
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".