Constructing Beauty: The Photographs Documenting the Construction of the Bloor Viaduct
Bibliographic record
Abstract
Cet article est une étude de cas mettant l'accent sur une sélection de photographies prises par le défunt Arthur S. Goss, photographe de la ville de Toronto, et portant sur la construction du viaduc Bloor.L'auteure examine l'importance du contexte politique et bureaucratique entourant la prise des photographies et se demande comment cette connaissance peut modifier l'interprétation et la compréhension de la narration du récit photographique.L'article soutient que l'objectif de la ville de Toronto en créant la série de photographies, c'est-à-dire documenter le progrès de la construction et illustrer la croissance de la ville, ne réflète qu'une partie du récit des faits et que ce n'est que quand les archivistes et les chercheurs prennent en compte le contexte fonctionnel de la création que les photographies peuvent le mieux être utilisées pour éclairer une partie de l'histoire.ABSTRACT This article is a case study that focuses on selected photographs taken by the late City of Toronto photographer Arthur S. Goss which document the construction of the Bloor Viaduct.The paper considers the importance of the political/bureaucratic context in which the photographs were taken and how this knowledge may affect the interpretation and appreciation of the photographic narrative.This paper contends that the City of Toronto's civic agenda in creating this photographic series -to record construction progress and illustrate the growth of the City -is just one part of the entire narrative, and it is when archivists and researchers take the functional context of creation into consideration that they can use the photographs for supplying a part of the story most effectively. Michael Ondaatje's novel, In the Skin of a Lion 1 describes the urban develop-* This paper is based on a presentation made to the Association of Canadian Archivists on 23May 2002 in Vancouver.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".