Bibliographic record
Abstract
Looking through the pages of family photo albums or the folders of photographic archival fonds can only be described as holding history in your hands. Whether it is in the form of colour or black and white prints, negatives, or slides, these photo-objects carry histories of lives lived that go beyond their frames. Focusing on a set of oral history interviews conducted with two Black women living in Montréal — a community photographer or image “maker” who was most active during the 1970s–1990s and a photo-collector or “keeper” who is currently active in preserving and sharing photographs for her church and wider communities within the city — this article engages with how the interweaving of photography and oral history gives us a rich way to experience the histories of Black social life in Montréal. Photo-led oral history interviews are sites for fruitful and in-depth conversation, providing interviewee and interviewer alike with the possibility of coming into encounter with everyday or minor histories that are too often overlooked. Moreover, this article is driven by a set entwined questions: How does oral testimony open up additional avenues for sharing the events of the past that have been captured through photographic images? What affective and relational qualities do photographs possess and how, in turn, do these qualities transform the space of the oral history interview? And, most urgently, why was photography used by Black Montréalers as a tool and a practice to remember and insist upon their collective presence?
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.021 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".