Relevance of Georg Grosz’s Weimar-era drawings to promoting social justice and health equity in contemporary society
Bibliographic record
Abstract
The arts and humanities can direct attention to the health-threatening effects of adverse living and working conditions and the political and economic systems that spawn them. Most of these efforts aim to improve healthcare by promoting empathy and sensitivity among health professionals towards patients and improving clinical skills. However, less effort is devoted towards improving living and working conditions-the structural and social determinants of health-that cause illness and make managing illness difficult. Using the arts and humanities to suggest how society could be changed to promote health is even less common, especially in regard to our economic system of capitalism. In this paper, we consider how the acerbic art of Georg Grosz, which critiqued the political, economic and social life of Weimar-period Germany, may find renewed relevance to the contemporary scene in Canada and other nations under the thrall of neoliberal approaches to governance. We suggest that Grosz's art can be a rich stimulus for promoting social justice and health equity through reflection and discussion, research, and then action to direct attention to how living and working conditions threaten health and how the economic and political systems that create these health-threatening conditions can be reformed or replaced. These activities can take place in classrooms, as part of professional development activities, or form the basis of research studies and advocacy efforts. Evidence of the usefulness of this approach obtained through discussions with undergraduate health studies students is presented.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".