The Colonial Legacies of the Digital Archive: The Arnold Lupson Photographic Collection
Bibliographic record
Abstract
This article explores the transformative ef fects of digitization on photographs by tracing the history of one series of photographic images, the Arnold Lupson collection, at the Glenbow Archives in Calgary, Alberta. As Lupson’s photographs of First Nations peoples, originally taken in the 1920s, moved through dif ferent hands and archival grids, the meanings attached to the photographs were reworked and renegotiated, and remnants of these earlier interventions continue to haunt the digital databases that now bear the cultural weight of these photographs. It is ar gued that in order to fully grasp these colonial legacies, we need to be able to reconnect the material history of the photographs more overtly to their virtual surrogates. RESUME Ce texte explore les effets transformateurs de la numerisation sur les photographies en examinant l’histoire d’une serie d’images photographiques, la collection Arnold Lupson, deposee aux Archives Glenbow a Calgary, en Alberta. Les photographies de Lupson, qui ont ete prises dans les annees 1920, montrent des peuples des Premieres Nations. Au cours des annees, des personnes travaillant selon differents courants archivistiques ont laisse leur marque sur les descriptions de ces photographies, qui ont ete retravaillees et modifiees. Des vestiges de ces premiers efforts descriptifs paraissent toujours dans les bases de donnees numeriques qui portent maintenant la marque culturelle de ces photographies. Le texte conclut que pour mieux comprendre cet heritage colonial, nous devons etre capables de faire le lien plus ouvertement entre l’histoire materielle de ces photographies et leurs copies virtuelles.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".