James Bowery

"Throw Me To The Wolves & I'll Return Leading The Pack" is the best aphorism I've seen for the evolution of individualism. I hadn't run across it until a member of my "flock" chose it for the tattoo that best defines him.

@elonmusk A culture that breeds beauty out of the gene pool replacing it with images and robots must be destroyed.

Grok Imagine

"You have no idea the power you provoke."

It's amazing to me how little self-reflection there is among people interested in sociology. This is even ignoring the 800lb ALgorithmic Information Criterion for model selection Gorilla in the Room. 10s($T) ride on sociology "narratives" if not the world's fate and meta-sociology's study of conflicts of interest are all but non-existent -- except insofar as to pseudoscientific palaver dresses up in white lab coats. How about starting with "one dataset many analysts" and go from there, kids? After you've done that for a while, then you might realize why Hume's Guillotine may be the only thing that saves ya'll from the real guillotines. github.com/jabowery/Humes…

I keep wanting to share this recent post, and since X doesn't seem to want to stop devolving any time soon I might as well now. I spent a lot of time working on a concept of an idea of a prototype to push LLMs into the direction of applied social sciences.

@goldengoatguild There are those who get it and then there are those who Get It. 😇

@jabowery Hahaha 😂

If you kids can't use your brains to figure out you're supposed to Fight Fair one on one like the rest of the sexual vertebrates, Mom will just have to make girls with nose piercings take those primate neurons away so you can't figure out how to cheat. youtu.be/ChO586cR3hQ

@jm_alexia What do you think the conditional (ie prompted continuation) decompression of a Kolmogorov Complexity program of a training corpus does? Why do you think you were so successful with your approach?

Incredibly simple, but powerful idea : ask a model to combine or take inspirations from multiple previous answers in order to generate the next ones. Its very akin to population-based genetic algorithms.

Here's what happens to those young men if Humes's Guillotine prize incentives grab their attention: The most perceptive of them will not only see that directing their competitive masculinity for the prize will attack their mortal enemy, but they will be materially rewarded. This is similar to Letters of Marque and Reprisal against Barbary Pirates that have enslaved young women: The material rewards will also include many young women who are now enslaved to The Theocracy. Don't underestimate the value these young men can bring to everyone, including themselves, once correctly targeted and don't underestimate the destruction they can wreak if people like Richard Hanania misdirect their gifts. richardhanania.com/p/start-demago…

"Boomers" and indeed anyone young men might perceive as participating in castrating them, that aren't sending 10% of their income to The Fair Church℠ Hume's Guillotine prize awards are really asking for it. github.com/jabowery/Humes… fairchurch.org/Donate.html

The social pseudosciences comprise The State Religion. So-called "wokeness" finds its power to defy the consent of the governed as unrepentant sinners in its seminaries aka "policy think tanks" and "higher education." All churches but one capitulate to this Satanic Power. fairchurch.org/AProtestantIns… github.com/jabowery/Humes… Those who can pray should so so. Contribute to nuking The State Religion. fairchurch.org/Donate.html

import numpy as np from scipy.integrate import odeint import matplotlib.pyplot as plt # Time span (0 to 20 years) t = np.linspace(0, 20, 200) # Initial Conditions (2026 Estimate) # H (Asset Price): Normalized to 100 # W (Median Income): Normalized to 20 (Ratio H/W = 5, historically high) # F (Fertility): 1.6 (Below replacement 2.1) # E (Elite Instability): 50 (High) y0 = [100, 20, 1.6, 50] # Parameters alpha = 0.04 # Speculative momentum beta = 0.5 # Credit sensitivity gamma = 0.2 # Demand drag delta = 0.5 # Productivity wage growth N_sov = 1.0 # Normalizer for population R_nat = 2.2 # Natural fertility target kappa = 0.2 # Sensitivity of fertility to housing cost mu = 2.0 # Elite production from inequality rho = 0.3 # Elite dissipation rate # --- Scenario 1: Status Quo (Grievance Economy) --- def status_quo(y, t): H, W, F, E = y # Dynamics dHdt = (alpha * H) + 2.0 - (gamma * (H/W)) # High credit injection (+2.0) dWdt = delta # No dividend dFdt = 0.5 * (R_nat - (kappa * (H/W)) - F) dEdt = (mu * (H/W)) - (rho * E) return [dHdt, dWdt, dFdt, dEdt] # --- Scenario 2: Property Money (Liquidity Economy) --- def property_money(y, t): H, W, F, E = y Demurrage_Rate = 0.05 Dividend = (Demurrage_Rate * H) / N_sov # Dynamics # Speculation (alpha) removed, Demurrage added dHdt = - (Demurrage_Rate * H) - (gamma * (H/W)) + 1.0 dWdt = delta + Dividend dFdt = 0.5 * (R_nat - (kappa * (H/W)) - F) dEdt = (mu * (H/W)) - (rho * E) # Inequality drops, so E drops return [dHdt, dWdt, dFdt, dEdt] # Solve ODEs sol_sq = odeint(status_quo, y0, t) sol_pm = odeint(property_money, y0, t) # Plotting fig, axs = plt.subplots(1, 3, figsize=(18, 5)) # Plot 1: The Core Mechanic - UnAffordability (H/W Ratio) ratio_sq = sol_sq[:, 0] / sol_sq[:, 1] ratio_pm = sol_pm[:, 0] / sol_pm[:, 1] axs[0].plot(t, ratio_sq, 'r-', linewidth=3, label='Status Quo') axs[0].plot(t, ratio_pm, 'g-', linewidth=3, label='Property Money') axs[0].axhline(y=3.0, color='gray', linestyle='--', label='UnAffordable Limit (3x)') axs[0].set_title('Housing UnAffordability Ratio (H/W)') axs[0].set_xlabel('Years from Now') axs[0].set_ylabel('Ratio (Price / Income)') axs[0].legend() axs[0].grid(True) # Plot 2: The Biological Consequence - Fertility (F) axs[1].plot(t, sol_sq[:, 2], 'r-', linewidth=3, label='Status Quo') axs[1].plot(t, sol_pm[:, 2], 'g-', linewidth=3, label='Property Money') axs[1].axhline(y=2.1, color='blue', linestyle='--', label='Replacement Rate') axs[1].set_title('Fertility Rate (CORR Proxy)') axs[1].set_xlabel('Years from Now') axs[1].set_ylabel('Births per Woman') axs[1].legend() axs[1].grid(True) # Plot 3: The Political Consequence - Instability (E) axs[2].plot(t, sol_sq[:, 3], 'r-', linewidth=3, label='Status Quo') axs[2].plot(t, sol_pm[:, 3], 'g-', linewidth=3, label='Property Money') axs[2].set_title('Elite Overproduction / Instability Index') axs[2].set_xlabel('Years from Now') axs[2].set_ylabel('Social Friction Unit') axs[2].legend() axs[2].grid(True) plt.tight_layout() plt.show()

I really wish I could share with young people what I've learned even if only how to take advantage of LLM coding assistance in the present, let alone what they've never been taught about how civilization works.

Anything but fix the political economy! You'll have to forgive me for suspecting the same "demographic" that opposed me in 1992 is now scapegoating guys like me for what they did to young people.

Look, I understand "Kill The Boomers", but start with those that vote for more immigrants and that own rental properties, instead of the ones that can't afford food because of their rent increases due to immigrants combined with food cost increases. Then see how you feel. x.com/SenateGOP/stat…