4 ms·

Wouldn't this be the default scientific position? Or to take some of the hyperbole out of the statement, rephrase as: "is it time to assume that health research

Wouldn't this be the default scientific position? Or to take some of the hyperbole out of the statement, rephrase as: "is it time to assume that health research hypotheses are incorrect until a preponderance of data and reproducible studies prove otherwise?"

Dylan16807 5y ago
"preponderance" is doing a lot of work in that statement. I would argue that this is mostly about reevaluating our standards for preponderance. And it's really hard to know if a study is reproducible. We could assume everything is incorrect until it has already been reproduced by an unrelated party, and I think that would be a major change in thought.
ChuckMcM 5y ago
Exactly, that's the thing about science, nobody believes it until everything that has been tried to show it is wrong fails. I wish this were taught more in schools.
- hanniabu 5y ago
  Yeah but you also can't go test 100 previous studies that the work you want to do is based on before you can even start yours. That's extremely inefficient, wasteful, and will tremendously slow progress.
  - guscost 5y ago
    > That's extremely inefficient, wasteful, and will tremendously slow progress. Democracy is also “extremely inefficient, wasteful, and slow to progress”. A process with those deficiencies can still be the best available approach (although your example is perhaps too far in that direction).
A4ET8a8uTh0 5y ago
Scientific.. yes. But the studies are intended and/or used for a specific business purpose. The moment you recognize this simple reality, it becomes extremely difficult to take anything at face value. My wife is on the other side of the spectrum. She explicitly believes that companies/researchers/people generally want to do the right thing. It is infuriating, because my personal approach is my approach to games: 'shit, until proven otherwise'.
aqme28 5y ago
There's a pretty big difference between an "incorrect" hypothesis and "fraud."
- FeteCommuniste 5y ago
  Exactly. It's one thing to, say, do a study that arrives at wrong conclusions because of insufficient controls or subtle mistakes in statistics. Quite another to simply invent patients or make up numbers.

Dylan16807 5y ago

"preponderance" is doing a lot of work in that statement. I would argue that this is mostly about reevaluating our standards for preponderance. And it's really hard to know if a study is reproducible. We could assume everything is incorrect until it has already been reproduced by an unrelated party, and I think that would be a major change in thought.

ChuckMcM 5y ago

Exactly, that's the thing about science, nobody believes it until everything that has been tried to show it is wrong fails. I wish this were taught more in schools.

hanniabu 5y ago
Yeah but you also can't go test 100 previous studies that the work you want to do is based on before you can even start yours. That's extremely inefficient, wasteful, and will tremendously slow progress.
- guscost 5y ago
  > That's extremely inefficient, wasteful, and will tremendously slow progress. Democracy is also “extremely inefficient, wasteful, and slow to progress”. A process with those deficiencies can still be the best available approach (although your example is perhaps too far in that direction).

A4ET8a8uTh0 5y ago

Scientific.. yes. But the studies are intended and/or used for a specific business purpose. The moment you recognize this simple reality, it becomes extremely difficult to take anything at face value. My wife is on the other side of the spectrum. She explicitly believes that companies/researchers/people generally want to do the right thing. It is infuriating, because my personal approach is my approach to games: 'shit, until proven otherwise'.

aqme28 5y ago

There's a pretty big difference between an "incorrect" hypothesis and "fraud."

FeteCommuniste 5y ago
Exactly. It's one thing to, say, do a study that arrives at wrong conclusions because of insufficient controls or subtle mistakes in statistics. Quite another to simply invent patients or make up numbers.