Gendercare Gender Clinic
5 years helping Gender Dysphorics
Time-Delay
Phase Space Embedding for Gender Identity Formation Dynamics in Gender Space* g
*That is a
part of a full paper still in preparation*
Copyright ©2006:
Gendercare.com
Abstract:
Gender identity formation is a complex multifactor
process that starts with the egg inside the mother’s womb. As we described in a
separate paper [1], the Gendercare
Gender Clinic developed “unexpected
gender tests” (which we call the MFX and FMX tests for MtF and FtM respectively).
The results of these tests show there
are different typical dynamic process structures and age relations during gender
identity development. The mathematical approach we utilized was not derived from or based on any etiology
hypothesis for any Gender Dysphoria condition ( the approach is independent of any
nature vs nurture hypothesis). Due to the lack of enough data to use time-delay
embedding to generate phase space from time-series, we developed a simpler method
to generate phase space. Now we are proposing a method to generate a phase
space utilizing time –delay embedding, also in a simple way (Return Map, with
one single variable: gender as one single variable). These tests are performed
online, so any person with a computer and an internet connection, from any
place around the world, may access this resource for Gender Dysphoria and other
possible gender variance evaluation assistance.
Introduction
Let us consider
a family of systems and processes that develops (as human diversity develops
from human eggs) from an initial starting point or condition (a “source”).
Keep in mind that
such systems are very complex, and some characteristics could naturally diverge
or converge.
For example we
know all humans naturally diverge from each other in terms of many different
characteristics.
When they
diverge, they may diverge following some divergence structures, depending on
the system dynamics.
For example let
us consider two human identical twins, from the same human egg: in some
respects they will converge (general appearance for example, hair color, etc.),
but in other respects they will diverge despite having the same initial
condition.
A remarkable
example of divergence among identical male twins is that they will always have different
fingerprints. If one identical twin has a GID (Gender Dysphoria) and would like
to have a physical gender transition, the other has a large probability of also
desiring one (nearly a 55-60% probability according to some data from Dr.
Milton Diamond from University of Hawaii - via private communication), but ... also significantly, the brother has a
large probability of not desiring it!
The consequence
of these arguments & facts is: in complex issues, we have 3 main possible
complex processes & systems:
Gender identity
is the name we give to the core feeling of being a man (male & masculine)
or a woman (female & feminine).
A human feeling
is almost always a complex phenomenon, being based on some factors of which a
person is consciously aware, but mostly on others of which he or she is not
aware. Therefore we may surely say gender identity (GI) is the result of one or
more of these complex human formation processes.
Gender identity
formation starts with the development of the body during gestation, from one
particular human egg. It continues through 3 physical “sexual differentiation”
formation steps:
After some
decades of intensive research, starting with guinea pigs (Phoenix et al., 1959)
and later with rats (Dörner & Docke, 1964as well as Pfaff & Sakuma,
1979a,b, Ogawa et al, 1997, 1998a, 1998b, 1999), continuing with studies of
non-human primates (mainly Bonsall & Michael since the 80’s at Atlanta and
also Resko at the Oregon Primates Center), and more recently of humans
(cadavers) as Dörner in Germany, Gorski at UCLA, Swaab in Amsterdam, among
others and most recently living humans also (as Kawamura et al, 2001); we discovered
there are two very important additional hard-wired, physical & biological
gender differentiation steps about which we presently know very little:
We may also
surely say that environment is involved in gender identity formation... starting
with the egg, mainly during gestation,
and during childhood & adolescence also!
The 5 steps we
talked about are hard-wired biological ones; but even among them, one of the later ones may be very sensitive to the
mother’s emotional state during gestation (the emotional state of the mother
affects her immune system, which interacts with and may inhibit the endocrine
system of the fetus). In other words, even the hard-wired biological steps –
mainly the “basal brain step” -- may be affected by environmental factors,
including those that emotional disturbances of the mother may cause inside the
womb.
In addition
there are surely many other important less hard-wired variables such as:
In summary, we
do not know ALL of the POSSIBLE
factors and their relative importance; only some of the probable important
variables are available for studying the complex system of gender identity
formation.
Therefore Gender
Identity (GI) may be considered as the result of these processes: a
multivariate system with known & unknown variables -- a complex system and
developmental process that during gestation mainly has a hard-wired biological
character, but that also during gestation can be influenced by the womb
environment. Later, this process is affected by a lot of many environmental
influences during childhood and adolescence; such effects may continue on into adulthood,
and surely this process, that for some subjects may be marked by tension and
discord, ends at maturity, leaving traces of all the traumas and social
experiences of that complexity as scars that we may define mathematically as random instability.
But even with GI
development being so complex and having so many unknown variables … we may still
study it just as we may study the formation of a hurricane, even though we may
not know all of its generating factors and controls.
We can employ the
same reasoning for gender identity... we
may not know all the factors that define it, but we can understand the complex
dynamics of its formation, if we have adequate time series data (a series with
enough data to use time-delay embedding to generate Return Maps).
Obviously to
develop dynamic knowledge about a hurricane, we need an enormous amount of good
data… and to develop understanding of gender identity we have only a few units
of data available for each patient… but the reasoning is the same (and to study
GI we may consider gender as one variable when to study hurricanes surely we
have multivariable and much more complex systems).
By understanding
the dynamic results and characteristics, we can have better insight into the
causes and main factors important for gender identity formation.
Gendercare approach
to the problem
The eternal nature
vs. nurture debate is absolutely sterile for understanding gender identity
formation, because both are important, although one may be more important in
specific stages of life than the other. The crucial point is that gender
identity is a complex result of multiple factors which we can study without needing
to know its causes.
To study
dynamic processes such as gender identity formation we have to follow one of
three main procedures:
We worked in
the beginning with the most feasible idea given our situation: to discover a
model or to generate a large time series would be almost impossible, but to
generate some families of small time series for gender identity formation was
possible using a new measurement instrument we developed: our Gendercare
unexpected gender tests.
Gendercare MFX
(for MtF’s) and FMX (for FtM’s)
Unexpected Gender Tests
What are these
tests?
Developing the Method

The gender
identity trajectory (a time series) may show structures and typical patterns of
gender identity development. We can study these possible structures and
patterns using the theory of complex systems (allowing us to research whether
inner organization exists or not).
To study gender
identity using these theories we do not need to know its causes -- we only need
to know the results of the complex process as a time series (in a family of
time series with the identical or almost
identical original source). From that
analysis we may gain insight into the main factors that are important for
gender identity formation and later its stabilization or disturbance.
The MFX/FMX
trajectories generated a time-series with a few points for each patient.
We had two
possible ways to interpret a time series
:
--- We could utilize
the few points only and try to generate dynamic knowledge from them, as we
showed in our other work [1] or
--- We could utilize
a mathematical model, (a curve fitting model), for the gender trajectories, and
from that model generate a new
time-series , and then use a simple time-delay embedding technique considering the time-series data generated by the model
(that way generating a Return Map).
The latter is the new approach we present here.
.
Elimination of time: phase space diagrams &
embedding.
By seeing only
one trajectory of a result as a time series, we might not understand very well
what has happened.
Traditional
statistical analysis of time series shows us very little (we have very little
data, trend analysis means nothing for us and auto-correlation factors also
help very little ...).
A good
evaluation method is to proceed using topology (the mathematics of continuous
space and figures), eliminating time as a system variable (as for an ideal
pendulum representing a family of different levels of energy – see Stewart,
1989 [2]; Torres, 2005 [3]). The elimination of time is referred to here as
embedding and the result is that we obtain a Phase Space Diagram.
Unexpected Gender Phase Space Variables
The solution we
proposed in our previous paper [1] was:
• Using a simple embedding
function for our unexpected gender data:
•In our Phase Space
diagrams obtained from MFX tests we define the Y axis as unexpected femininity. For our FMX test we
define it as unexpected masculinity, and for both, we name it f(t), at time of
life t.
•On our diagram’s X axis,
we show the embedded function we call gender gradient:
Gender Gradient=
{f[t(n+1)]-f[t(n)]}/[t(n+1)-t(n)]
Typical Phase Space Diagram for Gendercare Tests

Understanding
the MFX test phase diagram:
•All sources are male (0
unexpected femininity at the Y axis);
•Near the source we see a
bifurcation... normal men (the yellow family of curves near the male pole) soon
split off from GID and GIDNOS ones (all other curves). Among the “normal men”
tested are heterosexual, bisexual and homosexual men. Based on these men we may
establish some divergence coefficients for the system, thereby using them as
controls.
•Later there is another
bifurcation, near age 7, between CD and
GIDNOS (TG) – all mixed up in pink; and
TS (almost all in blue). ...
•The TS curves in light
blue show a family with very consistent structure, while some curves (dark
blue) diverge from that structure, mainly after age 7-10. As we can see in the
figure, the closer the gender identity
is to the female polarity (>70% unexpected femininity), the more organized
or “strange” the attractor is, showing a chaotic and deterministic behavior
that means hard-wired factors are the most important ones governing those TS
situations.
•After some years (at age
> 10-14), mainly for GIDNOS, TG and CD (the pink curves but also some of the
dark blue TS ones) the structure loses inner strength, and a lot of random
factors, acting as late influences, may start interfering with gender identity
formation (late instability due to early traumas and late external
interferences).
•The same happens for some
TS subjects (light blue curves at late ages), but with much less intensity.
Our New
Mathematical Approach to define a Phase Space for GI
We start from the same
trajectory data from the same MFX/FMX tests.
But now, we begin by using Curve Fitting Software to try to generate new time-series data *
* Curve Expert 1.3 by Daniel
Hyams..*
In this way, from the original data we can interpolate a fitting function of the type
:
X= a + bY + c Y2 + d Y3 [a, b, c and d are parameters and 2 and 3 are
exponents]
(a cubic polynomial fitting curve)
From this curve we could generate a table of
data, with regular time delay (we tried 10 weeks, 54 weeks & 108 weeks as
time-delay = D).
With the data generated by these time-series we could use time-delay embedding, establishing a phase space (as Return Map) with the coordinates:
X=X(t)
Y=X(t-Dt)
Taking Dt as 10, 54 and
108 weeks to plot the Return Map** (these weeks are considered since conception
and not since birth)
For practical purposes we
consider Dt=108 weeks
** Considering gender
identity formation as a one variable only system (gender variation), the Return
Map will be very effective for our purpose**
When we intend to study possible
etiologies for the GI formation process we consider Dt=10 or even a lower
value, to try to study possible details of the generated phase space curves.
We plot these curves for
patients, and we obtain the following typical
result:
Generating the Return Map
for Gender Phase Space

From the identical source, the yellow curve shows the
Phase Space Diagram (Return Map) for
normal men or women (heterosexual, bisexual and homosexual) with Dt = 108.
The gray family of curves
shows the typical TS family also with the
same Dt value.
Sometimes, some patients
show unique curves such as:

Or for example also:

For these two figures, in
the same phase space (always considering a return map with Dt = 108 weeks),
with the yellow curve for normal people shown
for reference, we see curves that
are atypical for TS and we could
classify better as GIDNOS
In the first figure, the
patients identify themselves as TS but they do not show a typical TS development which means the therapist needs to evaluate them very carefully, because
we must not make mistakes here. Some of
them, through their anamnesis, may reveal what happened in their lives to
determine their particular GI development, but for others only the MMPI may be
able to explain some possible GIDNOS situations.
More detailed anamnesis,
MMPI verification, careful and detailed transition, light HRT with strict
supervision are always necessary for such patients, and sometimes, depending mainly
on the MMPI , a local psychiatric/psychotherapeutic face-to-face verification
will also be important.
The second curve shows
some GIDNOS situations in which the
patients are sometimes aware of their TG/CD condition, and sometimes plan to have SRS (sex reassignment surgery). This
shows the therapist the same thing: these
patients need special supervision and more detailed observation, and sometimes they
may need a local psychiatric/psychotherapeutic face-to-face supervision.
Most of Gendercare TS MtF
and FtM patients show typical TS patterns, and do not need supplemental local face-to-face supervision,
but when in transition they always need special strategy, special FFS (from
surgeons that know specifically FFS for MtF patients) and secondary surgeries and treatments and HRT-hormone-therapy
supervision, and finally the SRS surgical correction, when that is the goal of the patient.
Advantages of that new embedding procedure (Return
Map)
We work with more points
for each curve plot, so we may also use time-delay with equidistant points.
With the older “gender
gradient” approach, we used real measured values, but sometimes with an
irregular time delay. For example, if the patient is 18 at the time of testing, we will need to
compare him or her with another patient
for whom the last point represents age 65 for example (we compare the curves,
one that represents from conception to maturity and the other from conception
to adolescence only!), and these time discrepancies may generate some
distortions of the gender gradient calculations.
That old procedure
generated some curve distortions, which we can avoid with the new procedure.
Conclusion
With both methods, we have
the same curve aspects, but the new method is more practical than the older
one.
For GID diagnostics both methods
are very interesting, but the new one is more precise and practical (for gender
therapy and GI diagnostics) and the old perhaps better to evaluate some
etiology considerations.
With time we hope we will
have more time-series data, to develop better typical curves and curve-fitting
models for typical families of TS, CD, GIDNOS
and TG people and to study in depth the
same method for interxex gender evaluation.
Thanksgiving
We would like to thank
Sonia John for her editing of our English
text.
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