Bibliographic record
Abstract
This photo-essay considers the other lives of family photographs by offering an analysis of my mother's collection of professional studio portraits and other vernacular photographs shot between the mid 1950s and late 1960s. How do we read the photo-archive of an 'Indian' woman born in 1941 to parents who were wards of the colonial state? A woman who was one generation removed from the sugar-cane plantations and coal mines where Indians were indentured as a coercive labour force? Influenced by Santu Mofokeng's project The Black Photo Album and Tina Campt's method of 'listening to' rather than 'looking at' photos, I refigure the family photo-archive to produce The Brown Photo Album, which is an experiment in seeing and being seen. In a context where the institutional visual archives of colonialism and apartheid have trained South African publics to see and thus know the Indian in very specific ways, this article redirects us away from the violence of the visual to the relationship between race, aesthetics and affect. It positions the family photo album not only as an alternative archive of the Indian experience but also as an archive through which we can begin to comprehend the Indian experience otherwise. This project probes the making of Indianness in the Natal Midlands, shifting the lens from urban centres like Durban and Johannesburg. As a work in progress, I present The Brown Photo Album as an experiment, an iteration of a project, a praxis of refiguring family photos in order to understand what this archive can reveal about our past, presents and futures.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.002 |
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".