Stories of The PoCSverse

What has happened since the writing of The Joshua Tree:

All of the in-person lectures for 2021–2022 (with an occasional PoCS Classic episode).

Fair warning:

In short: What follows is video documentation of what happened, rendered as poorly made, slow TV.

This is what happens when we have maniacal recording of everything.

Please see slides and associated clips for a more organised entry into the PoCSverse.

Week 27, 2022/04/18 to 2022/04/22:

Slides covered:
Organizations

Lectures:
#52 (first 34 minutes):
Organizations and Correlated networks.



We explore the model of organizations introduced in the previous episode. By adding informal links to a substrate hierarchy, we find a basic typology which includes core-periphery networks, team-based networks, random networks, and and multiscale networks. Under high pressure message passing, a simulation of problem solving with great uncertainty, core-periphery and multi-scale networks fare well, but the only multiscale networks show resilience to catastrophic failure.

#51
Robust, deep-problem-solving organizations.



What kinds of organization networks are resilient to failure under pressure, and which ones do well when uncategorized failures, even catastrophes, occur? We talk about Toyota recovering from a manufacturing disaster, ambiguous problems, collaborative search for knowledge, Ronald Coase, transaction costs, the Bank of Evil, possible network structures beyond hierarchies, and more. How do we solve problems we can't even describe? How do we model this? Multiscale networks will be winners.

Week 26, 2022/04/11 to 2022/04/15:

Slides covered:
Lexical turbulence
Computational History

Lectures:
#50
Ousiometry of stories in 3D; Ultrafame: God, BTS, and Trump; Humiliation and Revenge.



#49
Mismeasuring word birth and death; Lexical turbulence; Ousiometry for the Discworld.



A cryptograph. What's being plotted here? We puzzle through.

The birth and death of words. Is language slowing down? It's complicated.

Forensic data science.

We uncover lexical turbulence (which would later lead to allotaxonometry and story turbulence).

The Historical Thesaurus: A thousand years of language evolution.

And then real-time ousiometric analysis of Terry Pratchett's Discworld novels. We play around.

Week 24, 2022/03/26 to 2022/04/01:

Slides covered:
Ousiometry

Lectures:
#46
Making papers for Telegnomic studies; closing thoughts on Ousiometrics; Emotions.



We work through GitHub, Overleaf, local systems, connecting things together.

The advent of meaningful life is a meaningful demarcation.

Shannon, McCullough, and … L. Ron Hubbard.

The wisdom of crowds versus the stupidity of the many.

Lectures:
#45
Paper writing; A universal LaTeX template; Ousiometrics of traits and characters.



How to write papers with bonus universal template.

Writing is coding.

The greatness of the gif, and the seal of approval.

TV show transcripts.

Back to ousiometrics. We find, amazingly, that the power-danger-structure formalism holds for traits and characters.

Week 23, 2022/03/19 to 2022/03/23:

Slides covered:
Ousiometry

Lectures:
#44
What day is it?; Nandor and Colin Robinson, Power-Danger-Structure everywhere.



Command-line exploration of synousionyms and antousionyms.

Doomsday method: Conway's method for figuring out what day of the week any given date is.

What We Do in the Shadows: Colin Robinson explains the current understanding of reality to Nandor. Not so much with the elephants and the turtle.

Power-Danger-Structure in other places:

- States of mind: The circumplex model.

- Alignment Charts from Dungeons and Dragons.

- The theory of human stupidity

- 800 Characters in 90 Storyverses: Buffy the Vampier Slayer, Pride and Prejudice, Harry Potter, Game of Thrones ...


Lectures:
#43
Furrie-purries and zag-zig; deeper into power and danger; the safety bias of language.




Week 21, 2022/02/22 to 2022/02/25:

Slides covered:
Happiness
Linguistic Pollyanna Principle: The positivity bias of language
The Lexicocalorimeter


Lectures:
#40
Online discussion about Russia's invasion of Ukraine.

#39
Mismeasuring toxicity, the geography of happiness, and then so many more emotions.



Terrible science leads to the wildly wrong finding that people from Vermont are the most toxic in online comments, while New Hampshireans are the least. We investigate the madness.

The geography of happiness with some amusing and peculiar media reactions.

An interactive visualization of happinesss in the US with instrument tunability.

More emotions: Fear, anger, disgust, sadness, surprise, happiness. Can we build a disgustometer? A rageometer? Probably not. We keep thinking.

Assignments for this week:
19: Bay of Squids
20: The Fungus Amongus

Week 19, 2022/02/07 to 2022/02/11:

Slides covered:
Happiness

Lectures:

#36
Blogs, SOTU, ranking presidents, and remeasuring happiness with words people use.



Storytelling by Wordle.

Headline gender biases around women, visualization by pudding.cool.

Wefeelfine, an origin story.

The positivity of presidents through State of the Union Speeches.

Happiness in blogs.

33:50 Rating US presidents on many dimensions, including luck.

Google books: Problematic temporal corpora.

Mechanical Turk and Artificial Artificial Intelligence.

Remeasuring expressed happiness and sadness. A new lens. Getting things right on the side of the words people really use.

#35
Abusive scientists. Trust. The continued search for happiness (really meaning).



Assignments for this week:
17: The Great British Fake Off
18: Zari, not Zari

PoCS Vol. 2 starts here with lecture #29.

Week 16, 2022/01/18 to 2022/01/21:

Slides covered:
Happiness

Lectures:

#30
Trying to find happiness in a box of semantic differentials.



#29
An introduction to an introduction for PoCS, Vol 2. A glimpse of happiness.



A meandering.

In some order:

Comments about the course.

Assignment 16 is first. We're still in PoCS.

Cryptic crossword skills.

Today's Trope: Complete Monster.

Dunbar's Number and other numbers of friends. How friendship counts scale with intensity. Possibly connection to May's 1972 paper on the robustness of complex systems.

Excess deaths. Nearly 1 in 100 in Bulgaria. Below Dunbar's number.

Seating patterns in lectures, and re-arrangement within this one.

A touch of happiness near the end.

Prediction of social phenomena is hard. Measurement of now, and the past, is hard.

Assignments for this week:
16: Wet Hot American Bummer

Week 14, 2021/12/06 to 2021/12/10:

Slides covered:
Superstars and Fame
Stories
Contagious stories
Complexification

Lectures:

#28
Stories: Power, danger, taxonomy, contagion. And why complexify?

We end our introduction to the course, which was the course.



#27
Superstardom and stories.



Assignments for this week:
14: Back to the Finale: Part II

Week 12, 2021/11/15 to 2021/11/19:

Slides covered:
Biological contagion: Unpredictability of pandemics.
Social contagion

Lectures:

#24
Narrative epidemiology and some sampling of social contagion.



Everyone is Jennifer or Jessica.


#23
Recording failure due to AirPods behaving badly about 30 minutes in.

In lieu of replay, we present a PoCSverse Classic™ Season 9 lecture:

S9E21: Modeling pandemics, then on to social contagion.



PoCS has been warning of the unpredictability of pandemics from 2007 on.

Assignments for this week:
11: Romeo v Juliet: Dawn of Justness
12: Necromancing the Stone

Week 11, 2021/11/08 to 2021/11/12:

Slides covered:
Overview: Part of the Deliverator's origin story.
Optimal supply networks III

Lectures:

#22
We discuss pandemics.




#21
Where to put things. The scaling of the supply most fair, and the supply to the most.



0:00 COVID numbers in Vermont, everywhere, how things are going.

8:37 Origin Story for the Deliverator: Bit by a radioactive book delivered by a brain surgeon.

12:00 How to optimally locate hospitals, schools, coffee shops, all the things. Connection to the HOT model and the equipartitioning of risk. Potential to work on residuals and human rights.

Marginalia: Where to put things sketch.

Assignments for this week:
11: Romeo v Juliet: Dawn of Justness


Week 10, 2021/11/01 to 2021/11/05:

Slides covered:
Small-world networks

Lectures:

For #19 and #29, please take in some PoCS Classic™, spread across three episodes.

1. Start at 58:00 here (last 17 minutes):
episodes/20a/

Then watch the following two lectures (about 75 minutes each):
2. episodes/21a/
3. episodes/22a/

Assignments for this week:
10: Mr. Parker's Cul-De-Sac


Week 8, 2021/10/18 to 2021/10/22:

Slides covered:
Fundamentals

Lectures:

#16
More ponderings on emergence, and the unknown limits to what we can understand



Marginalia:
The black box output.

#15
Data, Measurement, Mismeasurement of Complexity, and Emergence



Marginalia:

Assignments for this week:
08: The Good, the Bad and the Cuddly


Week 6, 2021/10/04 to 2021/10/08:

Slides covered:
Manifesto
Power-law mechanisms 3: The rich-get-richer model

Lectures:

#12
Scoring stories, more on the rich-get-richer mechanism, the catching of phrases



Marginalia: Survey says ...

#11
One page manifesto and the essential model of rich-get-richerness



Marginalia: Semantic differentials from Osgood et al., 1957.

Assignments for this week:
06: Guest Starring John Noble


Week 5, 2021/09/27 to 2021/10/01:

Slides covered:
Power-law mechanisms 1: Random walks
Power-law mechanisms 2: Variable transformation
Manifesto


Lectures:

#10
Random walks abound, the path of unexpected transfiguration, some manifestoing



0:00 A 10 year history of figure making.

6:46 Papers as figure delivery systems, and how to read a paper.

7:40 The Paper Shredder*.

15:30 Random walks in reality. Life and death. Basketball. How money moves around. Scaling relations.

44:20 Unexpected transfigurations: Transformation of variables as a pathway to heavy-tailed distributions.

56:25 Random teleporting can end suprisingly badly.

1:00:46 PLIPLO and MIWO.

1:02:27 Manifesto with free cryptograph and matching shovel.

Marginalia: Lake Champlain.

* Every two (or three or four) weeks, and in the grand tradition of courageous academics everywhere, we review the painstaking, meticulous work of others not present to defend themselves. Pure of motivation, we endeavor to instantly and yet casually see where the paper obviously goes wrong and how work we did 15 years ago contains the entire paper’s thesis as a footnote on page 17. Finally, based on a loudness of ritualistic chant measure, we decide whether the paper lives to be read again, or dies by shredding, cited nevermore.


#9
Some sensible and (very) silly scalings according to the Ministry of Random Walks



0:00 Allotaxonometry for NBA player's season points.

2:55 Power-law mechanisms part 1: Random walks. We define a simple random walk which will prove to be surprisingly rich (also, don't gamble): Unit steps on a discrete 1-d lattice with time ticking away discretely. We set a zombie texter off and start to think about where they could be after t time steps. We find that we expect them to be where they started but that their typical displacement from home grows as the square root of time (delightful and profound).

16:35 Plinko!

17:50 We visit the Snormals, a very boring mountain range, when the normal distribution shows up to describe where our zombie texter might be, probabilistically speaking. Binomials and not-really Pascale's triangle (Stigler!).

35:25 The probability of returning to the start is strange.

40:11 Neck ties, hexagonal lattices, and random walks. A brief diversion.

42:30 When will our zombie texter come back? Will they come back? The extremely curious problem of first return.

43:09 A diversion to examine Mr. Goxx in a box, a hamster-based trading algorithm. Who does God follow on Twitter?

46:40 We work through the problem of first return, developing a method of images kind of approach. A power-law size distribution appears with a very dangerous exponent. Some comments on what happens in higher dimensions and on networks. Invariant densities.

1:09:11 Random walks as natural structure: River network basin boundaries. Scaling exponents and scaling relations.

Marginalia: Pratchett the cat tips over a large cylinder. Because he's a cat.

Assignments for this week:
05: Bored On Board Onboard


Week 4, 2021/09/20 to 2021/09/24:

Slides covered:
Zipf's data
Allotaxonometry

Lectures:

#8
Allotaxonometry—The art of comparing complex systems.



0:00 Australian Rules Football: Some big grabs, and profiles in epic losing.

6:51 The New York Times Spelling Bee, a team effort.

13:06 Allotaxonometry. We open the big, big box of divergences. So many. We talk about the excellence of ranks, common-sense wise and statistically speaking. Some more considerations of allotaxonograph histograms. We build up the expressions for rank-turbulence divergence (RTD) and probability-turbulence divergence (PTD). We make them behave well in their limits, and find how PTD matches with a suite of established divergences. And we take in some example allotaxonographs with various parameter choices for tweets, Google books, Jane Austen, baby names, corporations, plants.

57:30 We end with flipbook inspections of how tuning the instrument works, and how baby names have changed in the US over a century. Jennifers of the 1970s, and the Aidaning.

Marginalia: Area professor finds Wifi.

#7
Lexical turbulence and allotaxonometry. Totally, totally real things.



You know, maybe it is season 17. After taking a look at more of Zipf's measurements of everything (obituary counts, freight between cities, marriages), and realizing that many students did all the hard work, we start to figure out how to compare size-rank (Zipf) distributions.for two complex systems. Might be the same system at two points in time, might be two distinct systems. One forest with the clock ticking or two forests. Allotaxonometry is the totally real, totally normal name, even if we did make it up. Other-structure-measurement. We'll get to many comparisons: Word use on Twitter and in Harry Potter, Baby names, market capitalization, jobs in cities, species in forests. We explain the scaling of lexical turbulence for texts, which will motivate our general understanding and harnessing of rank turbulence


Assignments for this week:
04: Beebo the God of War


Week 3, 2021/09/13 to 2021/09/17:


Slides covered:
Power-law size distributions
Zipf's data

Lectures:
#6
2021-09-16: Zzzzzzzzzipfffff distributions. Rank all the things. (COVID-19 is a conspiracy.)



#5
2021-09-14: Pigeons are smarter than humans. Also, the Statistics of Surprise.




Pigeons are smarter than humans. What did the class think about wealth quintiles, both real and wanted? Pigeons are smarter than humans. We talk about the Monty Hall problem. Pigeons are smarter than humans. We wade into the statistics of surprise with the strangeness of heavy tailed probability distributions. Pigeons are smarter than humans. An example festival: Earthquakes, Daniel Kahneman's citaceons and abyssal plane wrongnesses, wars, moon craters, and more. Pigeons are smarter than humans. Jacques Bailly can spell a great many words. Pigeons are smarter than humans. Complementary Cumulative Distribution Functions (pure poetry). Pigeons are smarter than humans.


Assignments for this week:
03: Legends of To-Meow-Meow


Week 2, 2021/09/06 to 2021/09/10:


Slides covered:
Allometric scaling

Lectures:
#4
2021-09-09: Excess COVID-19 deaths, scaling, and our problems with probability.




The Grim Scorekeeper: How many people have died above expected numbers during the pandemic, from all causes? Excess deaths is the most basic number we need to track, and we explore the Economist's efforts to estimate a range of around 10 to 20 million. Difficult accounting. We work through the rest of scaling: cities, Moore's law gone wild (some terribly small ranges), and types and tokens, Heap's law for Lego sets. Before starting on power-law size distributions, we entertain the horribleness of assessing seemingly simple probabilities.

#3
2021-09-07: Scaling, scaling everywhere, and not a drop of happiness to drink.




More examples from biology: Maximal speeds of animals with limits to hammer time if you're elephant. Onto physics and engineering with engines, nails, the law of gravity. Dimensional reasoning gives us the terribly named Buckingham pi theorem. We think about a platypus pendulum, estimates of top secret bomb energy from a magazine cover, the base units of things. Scaling for people: Cities, what makes them, what they need, what they produce. Burlington is a special residual, at least in one plot, in one paper from 2010.


Assignments for this week:
02: The One Where We're Trapped on TV


Week 1, 2021/08/31 to 2021/09/03:


Slides covered:
In Media Res (100 days earlier …)
Allometric scaling

Lectures:
#2
2021-09-02: "I've been scaling for a lecture like you"



Some housekeeping about the course, and then we start at the end again with some thoughts on how to do science. Ouroboros. Basic science is describe and explain. Then onto a festival of scaling. The very basics of allometry and isometry and then we deal out examples of scaling everywhere. Life and biology first.

#1
2021-08-31: Welcome to the PoCSverse



From inside the mask. General, rambling overview of Things. Website, assignment "Here I Go Again" (01). An In Medias Res bit. Hexagons. Rick and Morty. And then onto scaling. The brains is interesting (said the brain, so let's not forget that). Koalas are supremely stupid. Sound fixed in post for video bits.


Assignments for this week:
01: Here I go Again