Evoking Brecht’s <i>A Worker’s Speech to a Doctor</i> : developing clinical skills, deepening understanding and promoting action on living and working conditions, or mobilisation for system reform or transformation?
Bibliographic record
Abstract
Bertolt Brecht's 1938 poem 'A Worker's Speech to a Doctor' has been used by health educators to direct attention to the health-threatening effects of adverse living and working conditions. However, to date there has not been a systematic analysis of these evocations and their goals (eg, develop clinical skills through promotion of empathy, encourage action to improve living and working conditions, and/or calls for broad societal mobilisation for systemic reform or even replacement). Of particular concern and relevance is the context in which this poem is mentioned, how it was applied, and whether it is presented in fragments or its entirety, thereby leaving intact Brecht's critique of the capitalist economic system and its role in creating illness as well as the Doctor's complicity in this same system. This investigation revealed that while most of the 56 instances found in books, book chapters, journal articles, presentations, and blogs did draw attention to how living and working conditions shape health and in many cases their public policy antecedents, most did not include the entire poem, leaving out Brecht's critique and blunting his message. We suggest 'A Worker's Speech' and other Brecht's poems as a rich source for reflection, discussion, and action to promote health by health and social services workers, researchers, community activists, and the public.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.043 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".