Canadian inter-regionalism and shades of grey in Kate Beaton’s <i>Ducks</i>
Bibliographic record
Abstract
Kate Beaton’s 2022 graphic memoir Ducks recounts the author’s time spent working in Alberta’s oil sands boom in the early 2000s. Although it focuses on one woman’s experiences, Beaton’s work also helps readers to understand the broader eco-social impacts of oil sands work camps, which are characterised by significant gender imbalances, regional differences, and an industry culture more concerned with the optics of safety than with its reality. In particular, it is Beaton’s use of specific techniques drawn from comics and cartooning – including colouring, panel arrangement, and use of monochromatic pages – that prompts critical reflection on how the public sees oil workers and how they understand their own roles in relation to communities, both while on the job and long afterwards. Such improved understanding of everyday experiences of oil work in Canada will be key to generating public will to act compassionately and pragmatically as the climate crisis increasingly leads disparate parts of the country to experience similar phenomena, such as extreme weather and wildfires.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.040 | 0.018 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".