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crowd data is political. Political is center biased and center is timing
deterministic. Timing determines resistance/acceptance.
The variable with crows is the location of center.
On Sun, 29 Jan 2006, Klaus Backert wrote:
> Hi, Greg,
> Am 29.01.2006 um 00:57 schrieb Greg Hunt:
> > Crowds have different effects on the task. For one thing, they
> > average error, not just in the case of jelly beans, but also as a
> > software project estimation technique (its a bit sad that a
> > technical mailing list would have picked the jellybean example).
> > In this case, a crowd is an expert.
> See below please.
> > Depending on the social structure, a crowd can enforce simple
> > ideologies, the Wikipedia NPOV (and its associated assumption that
> > neutrality is possible) is a good example of this, and in that
> > context they also enforce filtering (see the discussion pages
> > associated with the Wikipedia article on the Holocaust - there is a
> > great deal of argument about who is an expert and who is not). The
> > experts in that case are assumed to have looked at primary sources
> > and in some sense have vasluable opinions. The participants in
> > that discussion tend to be talking about limited ranges of
> > secondary sources and they look to me more liked editors with
> > opinions, than experts themselves. Perhaps this is another
> > instance of the crowd averaging error? Certainly the discussion of
> > Irving and the other revisionsists reads that way.
> ... really sad, and you are true with your opinion about the
> participants, I think.
> > In the case of technical topics the quality of the content is
> > variable and dependent on the editors and editing process, the XML
> > article is far more comprehensive than the Mainframe entry for
> > example, which has a few eccentric statements in it (Speed and
> > Performance), but there is not much debate about the technical
> > facts, so the averaging process is easier. The mainframe article
> > probably looks the way it does because the crowd is smaller.
> > What I hope to get from an expert is fast coherence and quotable
> > opinions. The question about the choice of a self-selected group
> > or the individual expert seems to be whether you want your expert
> > to be an editor/filter or a creator. Crowds seem not to create,
> > but can filter very well within the limits of their social belief
> > systems (the Wikipedia NPOV for example constrains what can be
> > said). An individual expert has a clearer response time.
> > An interesting question is, what happens as the crowd gets smaller
> > - what is the threshold size for effective debate and filtering?
> > Greg
> If you would like to look at my posting in answering Vladimir
> Gapeyev, you will find something about bad experience with crowds I
> had in my business, and about some causes of the problems (I've
> learned a lot out of this crashed projects, which I won't discount).
> Interestingly these have all been project teams with the task to
> create something (organisation, data, and software).
> May be filtering versus creating makes the difference.
> About the software project estimation technique:
> About 10 years ago, I read about several computer science projects.
> They found a certain difficulty. Many software experts have had
> similar or even the same lessons, read the same books, partly talked
> to each other, used the same techniques, rules, patterns and
> paradigmes, etc. Because of this the estimates tended to be biased in
> the same direction in several case studies. These crowds didn't
> average the error, but on average produced one in the same direction.
> I think, this again is counter evidence against wisdom of the crowd
> without a lot of precautions - even when filtering information. And
> the causes are more social again.
> I hope it's easier today, when we have better access to software
> experts all over the world.
> Well, I'm not thrilled by this wisdom-of-the-crowd thing. But I'm no
> opponent. I hope it will work with the metadata dictionary wiki.
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