The artist biopic and posthuman feminism: <i>Maudie</i> (2016) as ‘bio-zoe-geo-pic’
Bibliographic record
Abstract
Abstract This article discusses Aisling Walsh’s 2016 biopic about disabled Canadian folk artist Maud Lewis, Maudie, as a ‘posthuman feminist biopic’. Reading the film through a posthumanist lens with reference to concepts such as posthuman feminism (Rosi Braidotti), transcorporeality (Stacy Alaimo), vibrant matter, thing power, assemblage (Jane Bennett), and companion species (Donna Haraway), it argues that the portrayal of Maud diverges from traditional artist biopics. While artist biopics usually strongly hold on to humanist values such as individuality and self-sufficiency, Maudie foregrounds ideas of relationality and collectivity. It emphasizes how the human (an artist in this case) is intertwined with the more-than-human-world and inseparable from its surroundings. The film creates an equilibrium between human and non-human elements, showing how the artist is embedded within the material realm. It portrays ‘things’ not as passive objects but as actants, suggesting that things, humans, and non-human animals are in constant relationship with each other. It reframes art not just as an individual human act but as the result of multiple human and non-human interactions. The article concludes that Maudie revises not only the conventions of the artist biopic subgenre but also opens up reflections on the term ‘bio-pic’, suggesting that it needs to be rethought to include the idea that humans are in constant relationship with each other, the non-human and the world. In this light, it proposes the term ‘bio-zoe-geo-pic’.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.024 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".