Kid President: The Aesthetics of Childhood in Political Cartoons
Bibliographic record
Abstract
Since the 2016 US presidential election, a number of political cartoons have been produced that depict Donald Trump as an infant or toddler. He is drawn in diapers and with any number of objects we associate with young children, as well as engaging in behaviours such as crying, whining, and melting down. As a genre, the political cartoon offers complex readings, yet this particular phenomenon, in its repeated renderings, seems to signal just as much, if not more, animosity toward children than toward Trump. The question is, who is the real object of critique in these visual displays? What are the assumptions that cartoonists have about children, and how is the child deployed in and through these images? In this work, we examined thirty political cartoons depicting Trump as an infant or toddler, along with related artifacts, dating from 2015 to 2018. We discuss the ways that the cartoonists rely on stereotyped affects and behaviours of childhood to express purportedly progressive notions of equity. The effect of this growing archive of images, however, may betray those objectives, instead enacting power over the figure of the child.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".