Kan Azuma’s Canadian Landscape Photography: An Other Gaze from Within / La photographie du paysage canadien de Kan Azuma : un autre regard de l’intérieur
Bibliographic record
Abstract
The NGC collection holds over one hundred works of Japanese photographer Kan Azuma (b.1946) whose practice has been often celebrated within the context of multiculturalist rhetoric.His photographs, created mostly during the 1970s, represent an affective visualization of the Canadian landscape captured through the diasporic lens of the artist, based on his phenomenological encounters with places he visited in Canada.The first in-depth interview with the artist, conducted through email correspondence in 2022 with the author, reveals many thought-provoking crevices between Azuma's actual experiences of the land and the reception of his work in the Canadian art scene.This interview was not intended to advocate a gesture of rediscovering an artist who does not claim a distinguished place in the history of Canadian photography.Nor does it aim to reinforce an inherited hierarchy imposed by the institutional narratives of the time that benignly delineated him as "an artistic other."Instead, it calls attention to the artist's voice and his creative agency, which is indispensable in collectively reimagining our diverse histories from a non-linear and multicentred perspective.Azuma's own account of his time in Canada sheds light on facilitating transtemporal spaces of encounters in art institutional contexts, embracing many individuals' stories of lived experiences through their own journeys.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.036 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".