The Arthur H. Tweedle Collection, Project Naming, and Hidden Stories of Colonialism
Bibliographic record
Abstract
This paper explores the digitized photographs captured by Canadian optometrist and amateur photographer Arthur H. Tweedle during his government-sponsored eye survey of the Arctic in the 1940s, and considers the impact digitization has had on the meanings and functions of these images. Held by Library and Archives Canada (LAC), Tweedle’s collection has been digitized as part of Project Naming¸ a photographic identification project that seeks to identify unnamed Inuit individuals depicted in images held by LAC. While Project Naming’s impact in terms of acknowledging the agency and identities of Inuit depicted in the archival record cannot be underestimated, it is also important to consider the ways in which Tweedle’s collection functions differently after being digitized, and to question the extent to which this new context has led to a reframing of the photographs’ meaning. Analysis of Tweedle’s photographs, and of the textual materials that accompany them in the archives, suggests that the removal of these images from their original context as part of a wider collection has hidden much of their colonial history from the public eye. While one might read the images on the LAC website as simply a visual record collected by a tourist, meant for compilation in a personal or family album, the undigitized textual records in Tweedle’s files suggest that they were used as part of a wider effort to depict Inuit peoples as “others” in Canada.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.044 | 0.049 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.006 |
| 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".