technology

The replication crisis is an ongoing methodological crisis in which the results of many scientific studies are difficult or impossible to reproduce. Because the reproducibility of empirical results is an essential part of the scientific method,[2] such failures undermine the credibility of theories building on them and potentially call into question substantial parts of scientific knowledge.

[...] Historian Philip Mirowski argues that the decline of scientific quality can be connected to its commodification, especially spurred by major corporations' profit-driven decision to outsource their research to universities and contract research organizations.

Publication bias. In theory, rejection of the null hypothesis should elevate confidence that observed effects are real and repeatable. But concerns about the dichotomous interpretation of NHST as ‘significant’ or not have been raised for almost 60 years. Many of these concerns stem from a troublesome publication bias in which papers that reject the null hypothesis are accepted for publication at a much higher rate than those that do not. Demonstrating this effect, Sterling analyzed 362 papers published in major psychology journals between 1955 and 1956, noting that 97.3% of papers that used NHST rejected the null hypothesis.

The high publication rates for papers that reject the null hypothesis contributes to a file drawer effect in which papers that fail to reject the null go unpublished because they are not written up, written up but not submitted, or submitted and rejected. Publication bias and the file drawer effect combine to propagate the dissemination and maintenance of false knowledge: through the file drawer effect, correct findings of no effect are unpublished and hidden from view; and through publication bias, a single incorrect chance finding (a 1:20 chance at α = .05, if the null hypothesis is true) can be published and become part of a discipline’s wrong knowledge.

Ideally, scientists are objective and dispassionate throughout their investigations, but knowledge of the publication bias strongly opposes these ideals. Publication success shapes careers, so researchers need their experiments to succeed (rejecting the null in order to get published), creating many areas of concern (middle row of Figure 1), as follows.

I'm so tired. I hate Googler Science.

This is bullshit hype nonsense, and the fact it devolves into an ad for "AI-powered" Pixel 9 is pretty telling.

This is still less shit than their arxiv "GenAI Game Engine" crap, but not by much.