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Science is science writing; science writing is science

Meehan Crist writes:

There is a belief, particularly prevalent among scientists, that science writing is more or less glorified PR – scientists do the intellectual work of discovery and writers port their findings from lab to public – but [Rachel Carson’s 1962 book] Silent Spring is a powerful reminder that great science writing can expand our scientific and cultural imaginations.

In short, science writing is science. OK, maybe that’s too strong: it’s possible to do science writing without adding scientific content, simply reporting on a research project: “Scientists at Lab X conducted the following neutrino measurements, which they say implies that . . .” But any science writing that weighs multiple sources: “Scientist X reports A. . . but Scientist Y is skeptical because B . . . Scientist Z expresses agreement with Scientist X but they have friends in common and work in the same subfield . . .”—that’s science, as ultimately the scientific claims come into the story. Or, to put it another way, you can’t isolate the science from the story. Good science writing recognizes that, and bad science writing is, arguably, just making assumptions about that, i.e. bad science writing is “science” too, it’s just bad science.

Also consider the reverse point: Science is science writing. With rare exceptions, it’s impossible to express a scientific result without explaining it. Even in pure math, we like to have a “heuristic” explanation to accompany the proof. I can’t separate my “science” from my “science writing”: they’re different shades of the same thing.

11 Comments

  1. Matt Skaggs says:

    Three types of science writing:

    1. Formal papers, written in the terminology your peers expect you to use.
    2. “Vulgar science” per Stephen Jay Gould, with similar technical content to category 1, but any specialist terminology is either avoided or carefully defined. Gould insisted that the word “vulgar” was not meant to be pejorative, but rather in the original meaning of “for the people.”
    3. Journalism of scientific advances. Too often journalists waste most of the column inches on manufactured controversy and content-free quotes instead of technical details. The preferred method for generating controversy is find-the-crank, where the journalist scours the globe for the one old curmudgeon who still thinks that mammals outcompeted the dinosaurs.

    I agree that categories 1 and 2 are mostly the same, hopefully our humble writer is not injecting a lot of extra speculation when they write vulgar science. But science journalism has a different goal, more readers but not necessarily better informed readers.

    • Andrew says:

      Matt:

      I think the bigger problem is the scientist-as-hero framework for reporting; see discussion here. Scientist-as-hero reporting has several problems: first, it leads to overstatement of results; second, it misrepresents the process of science; third, it gets scientists used to the idea of uncritical publicity, and then when they get any negative publicity they get personally offended.

    • jim says:

      I like your breakdown of science writing, but:

      A) I would modify #3 so that it’s not just “scientific advances” but all science in the popular press (newspapers, mags, ezines)
      B) Should #2 be two parts? IE, 2.1) Gould, Sagan, many others and similar; and 2.2) Matthew Walker and similar?

  2. AV says:

    Writing is speaking at length. To whom to speak without words.

    There is no rhetoric, & no delusion of self-evidence; there be – dialogue.

    The best I heard on science writing comes from @KristinSainani

  3. Ron Kenett says:

    woww. it took time but seems that my original attempts to push for qualitative descriptors of research findings, i.e. verbal expressions of research claims, is finally sinking in.

    Gelman writes: “Even in pure math, we like to have a “heuristic” explanation to accompany the proof.”

    Yes. This is the basis for my proposal on generalisation of findings. The blog in the link below starts with Sam Karlin’s views on heuristics but these days, even stanford professors do not know of him (on the basis of a sample of size 1…)
    https://www.linkedin.com/pulse/statistics-crossroad-generating-information-quality-ron-s-kenett/

    See also https://www.linkedin.com/pulse/ten-questions-statistics-data-science-2020-beyond-ron-s-kenett/
    and https://www.linkedin.com/pulse/pragmatic-view-role-statistics-statisticians-modern-data-kenett/

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