Rigging Academic Articles to be more Progressive

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I have previously discussed how articles are altered such that the conclusions appear progressive even though the data says anything but. My article on wikipedia in action is all about this, and my upcoming book Smart and Sexy, which will be published by Arktos, also discusses this with respect to intelligence testing and brain size measurements among many other things. The red pill subreddit recently had a confession of such manipulation by a firm which does team building training (archive in case first link gets lost). Though the source is ultimately 8chan, I have seen enough of this stuff elsewhere that I think that it is very plausible that this person is real and being truthful. The short of it is that males very clearly did better than females in an organized task requiring spontaneous coordination. The order of performance went all male–>mixed gender–>all female. Since that doesn’t work for pushing the narrative, nonsense factors were made to appear to be the most important so that it looked like the mixed teams did best. However, the data is still there and unchanged for those who pick at it and they will be able to see the male teams did have better performance. This is exactly what happened in the research paper I looked at with respect to racial relatedness in the wikipedia in action article. Though the writing seems to say people of different races can be more related than people from the same race, the data says the exact opposite. So, here too we will see another example whenever this “scientific” article is actually released. Keep an eye out for it because there is more than enough detail for us to look at their exercise description then trace it directly back to this confession. Having this in hand would be absolutely delicious.

Below, is the text of the original confession:

Alright /pol/, here is something to reinforce your opinions on women working in teams.

I am working as a team building coach in Germany. I hold courses for a company were teams are being tested and need to work together to fulfil their tasks. The goal is to have a better working team afterwards and to address problems within the team. Now before I get startet none of this is scientific. We use certain tests that need certain skills and are measured by certain factors, such as time needed, number of steps, etc. We record everything but it is not really a scientific test environment(no control groups, no randomization etc.)

To describe one particular exercise:

In a group of (usually) 16 people everyone gets blindfolded and gets an object. 4 people get the very same object. Now it is up to the people themselves to find the other 3 guys with the same object to form a group of 4 people and advance to the next excercise.

Now, the object is basically two dimensional and the key to finding your group is to count the edges. You cant see, but you can feel how many edges your object has. The perfect way would be to put a finger on one edge and then start counting the edges with your other hand until you know the number.

You can either tell everyone your method so time is not wasted(indicator of strong leadership skill) or you try to locate someone else, ask him for his number of edges and so on(poor leadership, no systematic working, you get the idea).

On saturday last week I had to finish a presentation(lll get back to that later, its the reason I post it here on /pol/) that was requested by a study group of the BMBF, the “Bundesministerium für Familie und Forschung”, Ministry of Family and Science here in Germany). We keep track of the performance of every team and have access to quite an amount of data. The exercise described has been done 356 times and I want to talk a little about the results.

All female teams did absolutely terrible. There are only very few instances in which the women figured out to count the edges and utilized the method to achive success, let alone figured out that someone should take the lead. Even with strong female lead a lot of women were unable to figure out how to count the edges without losing count. They were just starting to count the edges without indicating where they started. There were 2 reports of women claiming to have objects with more than 20 edges while the physical maximum is nine.

There is almost no difference between all female teams and female teams with strong female leadership. Strong female leadership does increase performance but only if detailed instructions are given by the female leader. It is necessary to describe the process step by step. The best performing all female team with strong female leadership did the following:

  1. Female leader commands everyone to be quiet several times while female are already discussing subjects not related to tasks.
  2. Female leader achieves silence, explains that you have to count the edges. She also explains the method.
  3. Female leader asks everyone to find other group members with the same number of edges.
  4. Chaos ensues. Female leader tries to get everyone to be quiet again.
  5. Female leader achieves silence and commands all with 7 edges to move towards her voice.
  6. Female leader appoints a sub leader for another number, asks group member to move towards the voice of the sub leader. Repeats the process several times until all groups are established.

Yet they are still the performing worse than mixed teams with male leader ship and a lot of mixed teams with poor male leadership. This is in stark contrast to an all male team with strong male leadership.

  1. Male leader demands silence right alter the tasks starts. There is no discussion, no period of figuring out who the leader is.
  2. Male leader says everyone should count the edges. There is no explanation of the method, yet there is no documented case in which a males failed to get the right number of edges.
  3. Male leader commands all 43 to move toward his voice, verbally appoints sub leaders for other groups while the other still move.
  4. Subleaders start to command their numbers to come close to their voice, it gets a little louder since 4 people are saying their number constantly.
  5. Groups are established.

This was the fastest documented case. Male teams with no strong leadership came in second. Someone usually yelled the method, everyone else copied it and then everyone just yelled his number until all groups were established. Mixed teams with (strong or poor) male leadership came in third, Mixed teams with strong female leadership didnt exist, it was always a male taking the lead or figuring out the method first, others copied it. Mixed teams with no leadership didnt exist either. Female teams with strong female leadership came in fourth and Female teams with no or poor leadership came in 5th by a long margin.

Now the problem lies within the results itself. They are considered sexist and discriminatory. It is not what the study group wants to hear, alter all it is for our super progressive government that sees women as superior to men and mixed teams as an ideal, which is why I was asked by my boss to make it look like mixed teams performed the best. I didnt want to fix the numbers, l just had to come up with something that made avarage results look good. So the number one indicator that determines whether it was a success or not is not the time needed, the efficency of the method or another metric. It is harmony within the group. display of natural leadership meaning no one forced someone else to listen to his opinion. Strong male leadership tended you yell out commands that addressed everybody and demanded certain actions while leadership in mixed teams usually asked politely. I also turned letting your fellow group members figure out the solution themselves, giving them time into a plus. Oh yeah, and creativity of solution, sehr wichtig.

Average became the new greatness. Mixed teams and female teams had top scores on all these feel good items, performance was ignored. lm about to hold this presentation later this week and hand over all the data. I am excited what they cook up with it but left a stinky trip mine in there. The numbers have not been changed and if they use this for any paper or recommendation in their proposals for new policies the compromising data is still in there.

So if you see someone claiming bullshit of women being superior or some shit you should take a closer look at the numbers. What was measured, how it was measured etc. lm pretty sure I am not the onyl one who riggs his data in a way that it looks better for the intended purpose.

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