accurate
Explanation
The Joke
A person asks why scientists always portray their work unrealistically in movies, saying it would be "so much better if they went for accuracy." A scientist responds with what accuracy would actually look like: "I would like to present my findings... Failure to replicate my results will have no negative impact on my career. Also, my death ray will not actually kill anyone. It will merely create vaguely suggestive correlations. Finally, this work was funded by a pharmaceutical company, making it possibly biased, and it was not pre-registered, so it could be the result of p-hacking." He then holds up a vial and adds that the "bullet-proof serum" still needs to be tested on a larger sample.
The comic takes the common complaint that movies portray science inaccurately and flips it by showing what a truly accurate depiction of modern science would look like -- and it turns out to be deeply uncinematic. Instead of dramatic breakthroughs, real science involves replication crises, conflicts of interest, statistical ambiguity, and incremental progress.
The Humor
The humor comes from the deflation of dramatic expectations. People who complain about scientific inaccuracy in movies imagine that "accurate science" would still be exciting, just more intellectually honest. Instead, the comic reveals that accuracy would strip away everything that makes movie science entertaining. Every trope of the movie scientist -- the death ray, the super serum, the dramatic presentation -- is undercut by the messy realities of actual scientific practice. The joke also serves as pointed commentary on real problems in modern science, including the replication crisis, p-hacking, pharmaceutical funding bias, and the lack of consequences for producing irreproducible results.
References
The comic references several well-known issues in modern scientific research. The "replication crisis" refers to the finding that many published scientific results cannot be reproduced by other researchers, a problem particularly acute in psychology and biomedical sciences. "P-hacking" refers to the practice of manipulating data analysis until non-significant results become statistically significant. Pre-registration is a practice where researchers publicly declare their study design and analysis plan before conducting the research, to prevent after-the-fact data manipulation.