Reconsidering the Canadian “Hinterland”: Visual Culture, the \nEnglish-Wabigoon River, and the Mercury Collection of Marion Lamm \n1945–1980
Bibliographic record
Abstract
This thesis examines select visual culture produced and gathered in response to one of Canada’s worst environmental disasters: the mercury poisoning of the English-Wabigoon River in Northwestern Ontario. This catastrophic event is the contextual and historical point of entry to explore two related visual records first, the dominant settler-colonial place image produced by industry and government stakeholders; second, a more complex image world discernable in a locally gathered archive created by citizen archivist Marion Lamm (1918–1997). These representations and narratives are examined at the intersection of Anishinaabe and settler-colonial histories and contexts that formed around the mercury case. I employ discourse analysis located in late capitalist visual culture and archival histories to examine ephemera, periodicals, photographic publications, and a film within broader cultural and environmental histories surrounding the English-Wabigoon River. The primary questions guiding this thesis are: Who and what defines a Canadian hinterland? From what positions are its stories told? Here I trace how the dominant, settler-colonial place image of industrial success and a tourist paradise is complicated and challenged by a record of locally gathered materials. Through transtemporal readings of a catastrophic event, I identify gaps between the local and translocal tellings. In doing so, I hypothesize that the visual record produced and disseminated by government and industry stakeholders presents a settler-colonial “hinterland” visuality that was incoherent with local realities.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Thesis on visual culture and archives surrounding mercury poisoning of the English-Wabigoon River; cultural and environmental history, with an archival dimension that does not make research practice its object.
The thesis studies visual culture and environmental history surrounding a Canadian disaster.
Visual-culture thesis on a Canadian environmental disaster; arts/history of place, not research systems.
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 | 0.004 |
| Science and technology studies | 0.031 | 0.026 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".