Family Photography and Persecuted Communities: Methodological Challenges
Bibliographic record
Abstract
This paper examines methodological challenges involved in conducting research on family photographs from persecuted communities, using Japanese Canadian photos as a case study. Approaching family photography as a social practice that instills dominant familial ideologies, the paper examines their "performative scripts" that arrange family members according to normative identities and roles. The paper argues that researchers are not immune to scripts that shape how and what we have been socialized to see (and not see) in family photos. The paper thus presents techniques to distance oneself from these performative scripts and one's involvement in their social and emotional dynamics. Once able to disentangle oneself from the genre's normative practices, the paper argues it is necessary to situate the photos in their social and political context of persecution and survival. Given the insular, inward looking character of family photographs, the paper concludes by calling for intersectional analyses, reflecting on how one might bring one's own family photos into engagement with the photos of Indigenous families and turns to those of the Skwxwú7mesh (Squamish) Nation.
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 | 0.133 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.023 | 0.043 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".