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  1. #11
    Senior Member edcoaching's Avatar
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    [QUOTE=ygolo;344661]

    Why is the FFM more "academically blessed?"
    There is such bias against a bimodal distribution in the psychological community for the reasons you listed that the FFM, coming from factor analysis, fits what they think they know as reality. There is still great prejudice against Myers as well because she wasn't a psychologist, even though she developed two statistical techniques that no one else used until they could use supercomputers...

    They also think an instrument should measure. Type instruments don't measure, they sort. One group or the other. Bimodal.

    Do you believe the use of either typologies leads to Self-fulfilling prophecies?
    If people use it to excuse their behaviors, yes. If people use it for development and growth, individually or in teams, no. I see people learn to operate out of their preferences when appropriate all the time (and thus move toward maturity)
    Although, I understand the statistics behind various factor analysis, I find psychometric papers hard to read, because of assumed knowledge of what particular letter-denoted variables are, and general use of psychometric jargon. Is there a good way to find out what factor models are being used, and what the original data sets, correlation matrices, or covariance matrices were?
    You'd have to find the manuals for the NEO-PI, Sloan (I think that's a separate one) etc.

    I'm not that big of an instrument buff--I can do what I do with or without an instrument and sometimes it's better to use nothing at all than to risk people feeling like an instrument is labeling them...
    edcoaching

  2. #12
    Senior Member Kora's Avatar
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    Now there's even a Step III? Oh wow.
    5w4 - Idiosyncratic/Leisurely/Dramatic
    It's the devil's way now.

  3. #13
    Senior Member edcoaching's Avatar
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    Quote Originally Posted by Kora View Post
    Now there's even a Step III? Oh wow.
    It's TOTALLY different. Not about finding 4 letters but about finding your best paths to development...
    edcoaching

  4. #14
    Senior Member INTJMom's Avatar
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    Quote Originally Posted by ygolo View Post
    ...
    My questions in general concerning the "validity" of personality systems
    Why are MBTI, DiSC, Temperament (all Myers-Briggs like), etc. more popular in corporations still?
    I'm not sure, but I suspect that they may be more heavily marketed, and that for various reasons.
    It takes a long time for new ideas to catch on.
    Do you believe the use of either typologies leads to Self-fulfilling prophecies?
    I have witnessed it a little bit of that on forums.
    I assume it happens with a very small percentage of the people.
    Do you believe use of either typology will do more harm than good?
    As in everything else, it depends what it is used for. I have heard of people suffering negative consequences in the workplace by being pigeon-holed by their superiors. That is definitely a danger. I think Type Theory should be used as a guide for understanding, not as hard and fast ruler for pre-judging. I believe Type Theory does much more good than harm. It fosters understanding and acceptance among people. In my own experience, understanding my childrens' types may be the single most helpful thing I have ever learned as a mother.

  5. #15
    Senior Member INTJMom's Avatar
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    Quote Originally Posted by edcoaching View Post
    ...
    Absolutely. It's the theory, not the instruments, that does the work. Here are some examples.
    • When I finally got teachers to grasp the different needs of Judging and Perceiving students at one school, the teachers worked to implement strategies that took the failure rate on science fair, ,history day, major reports, etc., from 30 % to 0-2%.
    • In a team where over 60% of the employees were siding with the "old" president who still worked there, I used type theory to help them understand and appreciate the style of the new president. The intervention was so lasting that other department chiefs had me work with their staffs.
    • One team's meetings had been ending in shouting matches. We did an afternoon workshop just on communication and at the end the biggest troublemaker looked at all the work posted around the room and said, "Can we always sit in our [ST, SF, NF, NT] groups so we remember that we actually speak foreign languages?" The employees asked to have me return for at least 4 other meetings, working on other issues with them.
    • One student, responsible for 50% of the referrals to the principal's office, learned about his own type and his best approaches to learning and so did his teachers. He was NEVER in the principal's office again.


    I could go on and on. Ethically used, type can help people understand each other's strengths in ways that can truly be constructive. Hope this doesn't sound like a lecture--it is true that it is often misused, so a lot of people have only had superficial experiences and have no idea how effective deep use of the theory can be...
    Thank you for sharing your experience with us.
    This part of your post reflects the very reason why I am so excited about MBTT!
    It has been a tremendous help in my life, and I wouldn't have half the success I have in my relationships if it wasn't for MBTT! and namely, Barron and Tieger's work especially.

  6. #16
    Senior Member edcoaching's Avatar
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    Quote Originally Posted by INTJMom View Post
    This part of your post reflects the very reason why I am so excited about MBTT!
    It has been a tremendous help in my life, and I wouldn't have half the success I have in my relationships if it wasn't for MBTT! and namely, Barron and Tieger's work especially.
    Yeah, Tieger's stuff is great...I've talked to lots of INTJ moms who were "saved" by type as they learned why the preschool years weren't quite as enchanting for them as they were for a lot of moms. One told me, "Crafts? Pouring juice? There aren't any goals in my day. I want to discuss the book I just read, learn something, explore something!" They so appreciated when their kids hit grade school...
    Last edited by edcoaching; 10-04-2008 at 08:03 PM. Reason: Forgot to reference Tieger
    edcoaching

  7. #17
    Senior Member ptgatsby's Avatar
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    Quote Originally Posted by edcoaching View Post
    They also think an instrument should measure. Type instruments don't measure, they sort. One group or the other. Bimodal.
    That should be binary, not bimodal... unless they introduced strength as a component, anyway, which would require it to measure, not sort. If they have, I actually have to reject the premise of sorting into two groups rather than comparative to population, since the distribution of the sorters do not indicate any preference of one dimension over the other in a bimodal fashion.

  8. #18

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    Quote Originally Posted by ptgatsby View Post
    That should be binary, not bimodal... unless they introduced strength as a component, anyway, which would require it to measure, not sort. If they have, I actually have to reject the premise of sorting into two groups rather than comparative to population, since the distribution of the sorters do not indicate any preference of one dimension over the other in a bimodal fashion.
    You get a spread because of noise and randomness in the environment. It is quite common in classification problems. Granted, I am coming from an an engineering background but the principles ought to be the same.

    For instance, when making a decision of whether or not there is an object in front of you based on the intensity of a reflected signal coming back.

    This is a statistical phenomenon. You will get a bimodal distribution of the signal coming back if you run experiments with a portion of the time with object there, and a portion without it there(proportions chosen according to prior likely hood of object being there). The reason is that the medium carrying the signal introduces noise.

    The less noise there is the more cleanly bi-valent the distribution will be. But a bi-valent (binary) distribution is a kind of bimodal distribution.

    Accept the past. Live for the present. Look forward to the future.
    Robot Fusion
    "As our island of knowledge grows, so does the shore of our ignorance." John Wheeler
    "[A] scientist looking at nonscientific problems is just as dumb as the next guy." Richard Feynman
    "[P]etabytes of [] data is not the same thing as understanding emergent mechanisms and structures." Jim Crutchfield

  9. #19
    Senior Member ptgatsby's Avatar
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    Quote Originally Posted by ygolo View Post
    You get a spread because of noise and randomness in the environment. It is quite common in classification problems. Granted, I am coming from an an engineering background but the principles ought to be the same.

    For instance, when making a decision of whether or not there is an object in front of you based on the intensity of a reflected signal coming back.

    This is a statistical phenomenon. You will get a bimodal distribution of the signal coming back if you run experiments with a portion of the time with object there, and a portion without it there(proportions chosen according to prior likely hood of object being there). The reason is that the medium carrying the signal introduces noise.

    The less noise there is the more cleanly bi-valent the distribution will be. But a bi-valent (binary) distribution is a kind of bimodal distribution.
    Good points, but I was only referring to the "model" being chosen to fit the data into.

    The question I ask you - why do you accept a binary/bimodal distribution as the model of choice? Do you see "sorting" as different than "measuring"? Are the traits fairly reduced to a 0/1 state?

    If you know that it should be bi-modal, then it works. Do you?

  10. #20

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    Quote Originally Posted by ptgatsby View Post
    Good points, but I was only referring to the "model" being chosen to fit the data into.

    The question I ask you - why do you accept a binary/bimodal distribution as the model of choice? Do you see "sorting" as different than "measuring"? Are the traits fairly reduced to a 0/1 state?

    If you know that it should be bi-modal, then it works. Do you?
    I see sorting as one form of measurement. It has to do with what possible values the actual situation would create. Probability theory, plus some basic assumptions followed with mathematical reasoning yields which model we use.

    In the case of detecting an object, I know it will be bimodal. The object is either there or not, and there will be noise. This follows from the understanding of the situation at hand.

    In the case of a coin-flip, we also know it will be bimodal (a Bernoulli distribution to be more precise.)

    In the case of defects in a part, or random events in a continuum, the distribution would be a Poisson distribution.

    One expects Gaussians when averaging or summing large number of quantities.

    One expects when multiplying random variable the the log of the resulting random variable will Gaussian.

    Gaussians also come up in linear regression. In fact, this is when Gauss introduced the distribution, when he created linear regression.

    An understanding of the problem at hand determines the distribution to use based on probability theory and plausible "first principles". It will often also give a-priori conditions. There is no getting around this problem. One always has to have assumptions about distribution based on some logical understanding before modeling. Believing that you don't have assumptions only means you don't understand your assumptions.

    If your intention is to sort. Your are likely going to sort to a finite number of categories. The "measure" in this case is discrete. But you have to have a way to make the measurement also. The measuring apparatus needs to be calibrated, and once you do, you will know what sort of distortion or noise the instrument will introduce. The laws of probability will then give you an expected kind of distribution and a-priori values for the parameters of the distribution. The data then modifies the distribution to give a "posterior" distribution.

    This actually a very interesting topic in itself. But I am probably belaboring something you knew, since this is introductory inferential statistics.

    Accept the past. Live for the present. Look forward to the future.
    Robot Fusion
    "As our island of knowledge grows, so does the shore of our ignorance." John Wheeler
    "[A] scientist looking at nonscientific problems is just as dumb as the next guy." Richard Feynman
    "[P]etabytes of [] data is not the same thing as understanding emergent mechanisms and structures." Jim Crutchfield

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