Decolonizing Family Photographs: Ecological Imaginaries and Nonrepresentational Ethnographies
Bibliographic record
Abstract
This article lays out my process of developing an ecological and nonrepresentational approach for conducting an ethnography of family photos as objects of investigation, practices, and sites for the making and remaking of decolonizing stories and histories. It is rooted in a three-part project on family photographs: first, an ongoing project with a three-generation Indigenous family who has a history with Canada’s residential school system; second, revisiting my own family photo albums that include photos of missionary nuns in my family who had worked in Indigenous schools and communities in the 1950s–60s; and third, the development of a politico-ethico-onto-epistemological approach for viewing and analyzing family photos and narratives from and about photographs. The article focuses on the latter two parts of this project. Informed by my reading of Lorraine Code’s “ecological thinking” approach to knowledge making, I bring Code into conversation with Phillip Vannini’s “nonrepresentational ethnographies” combined with new materialist writing on performativity and vitality; selected Indigenous scholars’ writing on ontological multiplicity, knowledge making as relationship, and the making of life worlds; Margaret Somers’s approach to nonrepresentational narratives and ontological narrativity; and Annette Kuhn’s work on analyzing family photographs and cultural memory. I demonstrate this approach through the analysis of one of my family photos. I also reflect on the ethical challenges of attempting to analyze a different kind of family photo, such as photos of residential schooling that are increasingly on display in media, online, and in public venues. I argue for the need to address representational issues of social injustice in nonrepresentational approaches and a recognition that there are sites and times—especially in cases of human rights abuses, violence, or trauma—when nonrepresentational ethnographies and narratives call for strategic negotiation with representation.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.018 | 0.033 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".