Visualising conflicts. An exploration of Canadian artist Mary Riter Hamilton’s paintings: herstory of the war
Bibliographic record
Abstract
This study is an attempt to probe into the value of paintings as historical evidence by locating the investigation in the realm of history from below. The article suggests a new reading of Canadian artist Mary Riter Hamilton’s immediate post-war paintings and their significance in mirroring her take on the war by exploring details of her life based on her biography. I transcend the literal iconographical interpretation of her images and attempt to delve into the ambivalent angle of the painter’s psychological impact on her works of art which was largely under-acknowledged in the recent historiography. The paper tackles the main problematic of how the conscious and unconscious in Hamilton’s paintings are yoked to create a visual historical text. It is argued that War Material’s, Sanctuary Wood, Flanders’ and Albert (Somme) Route d’Amiens’ connotations are more complex than solely representing the historical aftermath of the global conflict or the inter-war sentiments of sacrifice, victimhood, patriotism and commemoration. This investigation goes beyond these dimensions. It is anchored around one key theme of aesthesiology by tapping into the paintings through the prism of emotion. I examine the sub-themes of fear, anxiety and trauma which are the common denominator in the three paintings.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".