The Mocking Meme: Popular Darwinism, Illustrative Graphics, and Editorial Cartooning
Bibliographic record
Abstract
In the fall of 2000, Toronto Star cartoonist Theo Moudakis responded to a sudden escalation in the number and severity of traffi c accidents in the city with an editorial cartoon depicting three naked male fi gures lined up in profi le against a featureless background, and labeled, from left to right, ‘Modern Man,’ ‘Neanderthal Man,’ and ‘Toronto Drivers’ (Figure 8.1). The image is undeniably funny and effective, but the question is, why? There is nothing intrinsically humorous or even meaningful in the three fi gures taken individually, with the partial exception of the last one, and then only when we include the caption. Otherwise, it is simply a drawing of a chimplike animal that has picked up a set of keys. Nevertheless, the drawing as a whole delivers the instantly recognizable message that these vehicular yahoos are a degenerate form of human life. This reading does not have to be spelled out for us in detail: We grasp it immediately as an inversion of the classic “Ascent of Man” illustration that has for decades been reproduced in magazines, textbooks, journals, and even museum dioramas as a kind of visual shorthand for the idea of evolution in general, and of Darwinism in particular. For the cartoonist, it is precisely this widespread familiarity that allows him to both reference and play with the image in creating his deliberately judgmental message. The question remains, nonetheless, as to how, when, and why certain kinds of imagery acquired not only a near-universal association with Darwinism, but also a decidedly evaluative functionality. How, in short, did popular Darwinism become not only a standard referent in Western visual culture but also, more specifi cally, a ‘mocking meme’ in the cartoonist’s toolbox? This essay addresses these questions, if only provisionally.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".