Bibliographic record
Abstract
In Raw Histories, her 2001 compendium of essays on photography, anthropologist Elizabeth Edwards writes of the layers of historical significance and meaning that colonial photographs bear. She elaborates: During the hours, days and months spent in many places, working with photographs … I have talked to people looking for ‘history’. This history has been both the actuality of evidential inscription, and their own particular ‘realities’. They are looking for their own history or someone else’s history, for the history of their discipline, or confronting the nature of their colonial past, both the colonised and the colonisers; people looking for their ancestors, people making, re-making or even imagining histories.1 Edwards succinctly gestures towards the many stakeholders of the colonial photographs: museum professionals, historians and anthropologists, but equally the descendants of the subjects of these images who find traces of themselves in imperial archives. The passage refers to efforts to prize alternative histories away from dominant narratives of colonial vision and its encyclopedic logic. It also refers to ongoing efforts to bestow personhood, lineage, and afterlife to the sitters of imperial images, the majority of whom were photographed in the context of great asymmetries of power. These alternative practices of reading photographs against the grain as a way of resuscitating Indigenous-centred narratives do not as often make it to the page. In the immense wealth of scholarship that colonial photography has generated, from studies that centre the performance of savagery to the development of exoticist codes, to the efforts of colonial officers to produce encyclopedic albums, literature concerning Indigenous revisions and interventions in the material as a means of challenging colonial epistemologies is less prominent.2 This begs the question: has the dominant literature in this area facilitated enough of a shift in methodologies to prioritise the non-colonial, entangled histories of these photographs? How can archival and art historical method be transformed to accommodate narratives of the photographed?
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.474 | 0.171 |
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".