[HN Gopher] How 'animal methods bias' is affecting research careers
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       How 'animal methods bias' is affecting research careers
        
       Author : LinuxBender
       Score  : 30 points
       Date   : 2025-03-21 19:51 UTC (4 days ago)
        
 (HTM) web link (www.nature.com)
 (TXT) w3m dump (www.nature.com)
        
       | mschuster91 wrote:
       | > In general, Krebs says, NGO grants for animal-free research
       | tend to be smaller than the longer-term, multimillion-dollar
       | awards offered by government sources such as the US National
       | Institutes of Health (NIH), the world's biggest funder of
       | biomedical research.
       | 
       | ... for now. Given the widely circulated "naughty words" list for
       | grants [1], I would not be surprised at all if this kind of
       | research gets labeled and discarded as "woke" just as well.
       | 
       | [1]
       | https://www.forbes.com/sites/brucelee/2025/03/15/these-197-t...
        
         | DrNosferatu wrote:
         | With that terms index, there will be no more mathematical
         | statistics research!
        
           | mschuster91 wrote:
           | Pushing FUD on the entire academic sector, that's what it is.
           | Pressure people into absurd self-censorship.
        
         | DecentShoes wrote:
         | Should've thought of that before they started punishing
         | scientists who dissented from gender ideology. Something had to
         | be done to stop it stomping further on the rights of women,
         | children, and gay people.
        
       | SpicyLemonZest wrote:
       | I'm a bit confused on whether "other models that may more
       | reliably mimic human biology" generally exist today. The article
       | mentions a couple non-animal models, but do we know that they
       | _are_ better analogues, or are they just ideas of where research
       | might go if people didn 't expect in vivo results? The point of
       | in vivo studies, after all, is that it's easy to build artificial
       | models which accidentally strip out some important complicating
       | factor.
        
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