Heisenberg: Surf the Wave-Particle (Confidence Tradeoff)

[Heisenberg]

Any kind of function combining a variety of different variables (especially with PCA) should have the values normalized between some values ([0,1]) to make sure the wider range of values specific variables can take on don't lead to "assigning more credit" to the variables contribution as PCA provides the dimensions of greatest variance.

Of course there always is the option of using neural networks and let it figure it out but that would still require class/numeric labels (the function output value) for each feature vector.

[Heisenberg]

If the driver is typically the younger generations that get the short end of the stick in may be helpful to limit the analysis to these groups. At the least try to narrow it to the groups that get effected the most. The corruption and negative consequences will probably vary culture to culture but as John has alluded to finances drive a large portion of it. I think the question to ask is what will drive the frustrations. I'm sure things like wealth/income inequalities along with youth unemployment/underemployment rates could be a start, perhaps upward mobility too. Maybe even personal debt. These factors would also vary based on geographic regions and the economic landscape. I think fear and a sense of hopelessness drive a good portion of it. The more that this can be quantified in the various population groups could prove useful.

[Heisenberg]

Singular value composition (SVD) can also be useful with dimensionality reduction https://www.youtube.com/watch?v=P5mlg91as1c.

Also important to remember images are a combination of many dimensions i.e. images are composed of a Red Green Blue spectrum (or HSV, etc.) and these are combined to give the final picture. May be helpful to just focus on figuring out the "intensity" value for each dimension of your emotion(?) space and stack them on one another.

[FishbellykanakaDude]

Any kind of function combining a variety of different variables (especially with PCA) should have the values normalized between some values ([0,1]) to make sure the wider range of values specific variables can take on don't lead to "assigning more credit" to the variables contribution as PCA provides the dimensions of greatest variance.

Of course there always is the option of using neural networks and let it figure it out but that would still require class/numeric labels (the function output value) for each feature vector.

..yeah,.. and the difficulty of getting "success quality" outcomes,.. meaning "What qualifies as a success that the net can learn from?"

Although having enough real-life observations would provide that data, assuming that the technician's version of "a win" is correct.

[FishbellykanakaDude]

If the driver is typically the younger generations that get the short end of the stick in may be helpful to limit the analysis to these groups. At the least try to narrow it to the groups that get effected the most. The corruption and negative consequences will probably vary culture to culture but as John has alluded to finances drive a large portion of it. I think the question to ask is what will drive the frustrations. I'm sure things like wealth/income inequalities along with youth unemployment/underemployment rates could be a start, perhaps upward mobility too. Maybe even personal debt. These factors would also vary based on geographic regions and the economic landscape. I think fear and a sense of hopelessness drive a good portion of it. The more that this can be quantified in the various population groups could prove useful.

You (Heisenberg or John) could (almost certainly) tease out all the "dimensions" (physical conditions) that are the "drivers" for the "emotions" (frustrations of various types, hatreds, resentments, risk aversion, status quo inertia, etc) for the various populations, and sub-populations, involved in a "local" (however defined) "conflict potential" scenario.

That would be quite the fascinating matrix!

..and,.. just to be cheeky,.. perhaps base the "emotions" off of some elaboration of "The Big Five Aspects" of personality?
(( see https://understandmyself.com/personality-assessment , which IS a Jordo Peterson thing.. ))

• Enthusiasm (spontaneous joy and engagement) and Assertiveness (social dominance, often verbal in nature) for Extraversion.
• Withdrawal (the tendency to avoid in the face of uncertainty) and Volatility (the tendency to become irritable and upset when things go wrong) for Neuroticism.
• Compassion (the tendency to empathically experience the emotion of others) and Politeness (the proclivity to abide by interpersonal norms) for Agreeableness.
• Industriousness (the ability to engage in sustained, goal-directed effort) and Orderliness (the tendency to schedule, organize and systematize) for Conscientiousness.
• Openness (creativity and aesthetic sensitivity) and Intellect (interest in abstract concepts and ideas) for Openness to Experience.

..yet another wacky idea from your favorite flounder!

Perhaps sailing out to Tabuaeran to live might work out? Whatcha think?

Aloha! <shaka nui!>

[Heisenberg]

https://hbr.org/2015/11/the-new-science ... r-emotions

The process of quantifying and creating models around emotions seems like the territory of marketers and political analysts. If anyone knows one it may be helpful to try and re-purpose what is known into the context of GD than trying to reinvent the wheel. Definitely a hard question.

Question for John:
In thinking about the emotions that identity groups go through is it a semi strict sequential movement from denial to anger (or some other sequence)? Or is the model for thinking about it more like grief where there is denial, anger, depression, bargaining, and acceptance and an identity group will go through many of these emotions at different points before finally moving into "acceptance"?

[John]

> https://hbr.org/2015/11/the-new-science ... r-emotions

> The process of quantifying and creating models around emotions
> seems like the territory of marketers and political analysts. If
> anyone knows one it may be helpful to try and re-purpose what is
> known into the context of GD than trying to reinvent the
> wheel. Definitely a hard question.

> Question for John: In thinking about the emotions that identity
> groups go through is it a semi strict sequential movement from
> denial to anger (or some other sequence)? Or is the model for
> thinking about it more like grief where there is denial, anger,
> depression, bargaining, and acceptance and an identity group will
> go through many of these emotions at different points before
> finally moving into "acceptance"?

The denial to acceptance sequence for individuals doesn't really
apply to entire populations, since each person in the population
will be at a different step in the sequence, so you get an
averaging effect.

However, there is an entirely different sequence of emotions that I've
described before.

From the point of view of Generational Dynamics, both controversy and
euphoria are to be expected at a military attack that could begin an
all-out war. Any military attack is going to be controversial, but
the population can also easily become heavily invested and become
euphoric.

Here's how historian Wolfgang Schivelbusch describes how the euphoria
at the beginning of a war is itself highly delusional in his 2001
book, The Culture of Defeat: On National Trauma, Mourning, and
Recovery:

> The passions excited in the national psyche by the onset of war
> show how deeply invested the masses now were in its potential
> outcome. Propaganda had reinforced their conviction that
> "everything was at stake," and the threat of death and defeat
> functioned like a tightly coiled spring, further heightening the
> tension. The almost festive jubilation that accompanied the
> declarations of war in Charleston in 1861, Paris in 1870, and the
> capitals of the major European powers in 1914 were anticipatory
> celebrations of victory-since nations are as incapable of
> imagining their own defeat as individuals are of conceiving their
> own death. The new desire to humiliate the enemy, noted by
> Burckhardt, was merely a reaction to the unprecedented posturing
> in which nations now engaged when declaring war.

The euphoria goes on until something goes wrong, usually some kind of
military disaster, such as the Battle of Bull Run in 1861 or the
Bataan Death March in 1941, and then the euphoria turns to panic.

The panicked reaction can be much greater when a military disaster
occurs. In his 1832 book, On War, General Carl von Clausewitz
describes what happens:

> The effect of defeat outside the army -- on the people and on the
> government -- is a sudden collapse of the wildest expectations,
> and total destruction of self-confidence. The destruction of
> these feelings creates a vacuum, and that vacuum gets filled by a
> fear that grows corrosively, leading to total paralysis. It's a
> blow to the whole nervous system of the losing side, as if caused
> by an electric charge. This effect may appear to a greater or
> lesser degree, but it's never completely missing. Then, instead of
> rushing to repair the misfortune with a spirit of determination,
> everyone fears that his efforts will be futile; or he does
> nothing, leaving everything to Fate.

From the point of view of Generational Dynamics, the events that cause
this "sudden collapse" and "total destruction" of self-confidence are
called "regeneracy events," because the panicked reaction regenerates
civic unity for the first time since the end of the preceding crisis
war.

[Heisenberg]

This would lead me to believe that what matters is an individual's view of their identity group and its survival being the important part to model. In that case then re-purposing what is known about the "radicalization" process of muslims would prove pretty useful if it could be extended to large groups of people. Essentially the same process just a different identity group's "propaganda". I'm sure there are some neat tools and models that already exist in this space. Yasmin Green @ google is leading a team in this area.