Meta-Parasitism: Systemic Failures of Extractive Economies

Contemporary capitalism functions as a runaway recursive process that accumulates capital faster than ecological and social systems can regenerate. Using the Recursive Generative Emergence framework, we formalize this dynamic as meta-parasitism and derive thresholds at which extraction shifts from sustainable to collapse-prone. We show how Justice–Cooperation–Balance (J-C-B) reintroduces the negative feedbacks required for long-term persistence.

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\title{The Meta-Parasite:\\Runaway Recursion and the Systemic Failure of Extractive Economies}
\author{C.\,L. Vaillant}
\date{}

\begin{document}
\maketitle

\begin{abstract}
This paper extends the Recursive Generative Emergence (RGE) and Recursive Collapse Model (RCM) frameworks to the socio-economic domain, diagnosing contemporary capitalism as a runaway positive-feedback recursion that undermines the ecological and cognitive systems upon which it depends. Through systems-theoretic modeling and ecological analogies, we formalize \emph{meta-parasitism} as the accumulation of capital beyond regenerative capacity, yielding collapse of host systems. We propose Justice–Cooperation–Balance (J-C-B) as stabilizing attractors for sustainable recursion, outline quantitative criteria for equilibrium, and suggest design principles for infrastructures that internalize externalities and restore generative balance.
\end{abstract}

\section{Introduction}
In nature every living system survives through feedback. Forests, coral reefs, and even single cells operate within recursive loops that balance growth with repair, competition with cooperation, and energy intake with entropy release. Wherever that balance fails—whenever one process amplifies without constraint—the result is collapse. Human civilization, however, has built an economic architecture whose central feedback, capital accumulation, behaves precisely like such a runaway process.

This paper extends the \textbf{RGE} and \textbf{RCM} frameworks from biological and informational systems to political economy. It proposes that contemporary capitalism is not merely an economic tool but a \emph{meta-parasite}: a recursive structure feeding on its own host substrates—ecological, cognitive, and social—at rates exceeding their regenerative capacity. Unlike self-correcting cycles in nature, this recursion lacks stabilizing attractors.

If recursive intelligence and cooperation are the universe’s most reliable designs for persistence, the current global economy presents an evolutionary paradox: a species capable of modeling feedback in exquisite mathematical precision has organized its survival around a structure that defies those same equations.  

\textbf{Research question:} How can the dynamics of accumulation, extraction, and regeneration be formalized as a recursive system, and what feedback constraints—mathematically and ethically—are required for such a system to remain generative rather than parasitic?

\textbf{Hypothesis:} There exists a measurable threshold of extraction beyond which socio-economic recursion transitions from generative emergence to collapse. When J-C-B are absent, stability disappears; re-introducing them restores the negative feedbacks that anchor the system.

\textbf{Contributions:}  
(1) Formal extension of RGE/RCM to economics.  
(2) Definition of meta-parasitism.  
(3) J-C-B as stabilizing coefficients.  
(4) Empirical and policy criteria for detection.  
(5) Ethical design translation.

\section{Background and Related Patterns}
Across scales—from protein folding to planetary climates—systems persist by embedding counter-forces that absorb fluctuations.  Negative feedback, mutualism, and redundancy are not moral choices but mathematical necessities.  Fire racing through dry brush, unchecked markets, or over-leveraged finance all exhibit the same pathology: positive feedback without damping.

\subsection*{Energy and Information Flows}
Following Prigogine’s \emph{dissipative structures}, order survives by exporting bounded entropy.  Beyond sustainable throughput, coherence disintegrates.  The free-energy principle in neuroscience mirrors this: agents minimize informational entropy through adaptive action; when feedback decouples, collapse follows.  Economies likewise accumulate “prediction error’’ when market signals detach from ecological cost.

\subsection*{Economic Analogues}
From Quesnay to Odum, economists likened value circulation to metabolism.  Industrial capitalism severed the regenerative loop: extraction → consumption → waste.  Value now replicates via replication—financial derivatives, data harvesting—rather than maintenance of the host.

\begin{table}[h!]\centering
\caption{Natural vs. Artificial Recursion}
\begin{tabular}{@{}lll@{}}\toprule
Property & Natural Recursion (Generative) & Capitalist Recursion (Runaway)\\\midrule
Feedback type & Negative/self-limiting & Positive/self-reinforcing\\
Energy–info budget & Conserves throughput & Consumes substrate\\
Diversity & Promotes resilience & Optimizes to fragility\\
Cooperation & Mutualistic networks & Competitive zero-sum\\
Temporal horizon & Cyclical/regenerative & Linear/extractive\\
Outcome & Homeostasis & Overshoot → Collapse\\\bottomrule
\end{tabular}
\end{table}

% Figure 1: Feedback taxonomy (background section)
\begin{figure}[h]
\centering
\begin{tikzpicture}[>=Latex, node distance=14mm]
\tikzset{
  box/.style={rounded corners, draw, thick, align=center, minimum width=36mm, minimum height=9mm, fill=gray!5},
  edge/.style={-Latex, thick},
  lbl/.style={font=\footnotesize, inner sep=1pt}
}
\node[box, fill=green!8] (neg) {Negative Feedback\\(self-limiting)};
\node[box, right=35mm of neg, fill=red!8] (pos) {Positive Feedback\\(self-reinforcing)};

\node[box, below=12mm of neg, fill=green!12] (nat) {Natural Recursion\\(ecosystems, metabolism)};
\node[box, below=12mm of pos, fill=red!12] (cap) {Runaway Recursion\\(extractive economy)};

\node[box, below=12mm of nat, fill=blue!8] (jcb) {Stabilizers:\\Justice--Cooperation--Balance};

\draw[edge] (neg) -- node[lbl, above] {homeostasis} (nat);
\draw[edge] (pos) -- node[lbl, above] {overshoot} (cap);
\draw[edge] (jcb) -- node[lbl, right] {damping, repair, limits} (nat);
\draw[edge] (jcb.east) .. controls +(18mm,0) and +(18mm,0) .. node[lbl, above] {counter-loop} (cap.east);
\draw[edge] (cap.west) .. controls +(-12mm,6mm) and +(12mm,6mm) .. node[lbl, above] {externalities} (nat.east);
\caption{Taxonomy of feedbacks: natural systems bias toward negative feedback (stability); extractive regimes amplify positive feedback (overshoot). J-C-B reintroduces stabilizing loops.}
\end{tikzpicture}
\end{figure}

\section{Formalizing Runaway Recursion}
Let \(A(t)\) = accumulation, \(H(t)\) = host capacity, \(R(t)\) = repair budget:
\[
\begin{aligned}
\dot A&=\alpha A\!\left(1-\tfrac{A}{\kappa H}\right)-\lambda R,\\
\dot H&=\beta R-\gamma A,\\
\dot R&=\rho H-\sigma R.
\end{aligned}
\]
Feasible equilibrium requires \(4\lambda R^*<\alpha\kappa H^*\).  
Violation defines meta-parasitism.  Local stability via the Jacobian yields
\[
\alpha < \frac{\gamma\beta\rho}{\sigma\lambda},\qquad \kappa H^*>2A^*.
\]
If \(\lambda\!\to\!0\) (no repair), \(\dot V>0\); collapse ensues.

% Figure 2: Phase portrait (A vs H)
\begin{figure}[h]
\centering
\begin{tikzpicture}
\begin{axis}[
  width=12cm, height=8cm,
  xlabel={$A$ (Accumulation)}, ylabel={$H$ (Host Capacity)},
  xmin=0, xmax=10, ymin=0, ymax=10,
  quiver/colored = {blue},
  axis on top, grid=both]
% Illustrative field using R* ≈ (rho/sigma) H
\addplot[->, quiver={
  u = (0.6*x*(1 - x/(1.2*y)) - 0.25* (0.5*y - 0.35* (0.5*y/0.35)) ),
  v = (0.4*(0.5*y/0.35) - 0.25*x), scale arrows=0.08}, samples=15, domain=0.5:9.5, y domain=0.5:9.5] {0};
% Stylized nullclines (illustrative)
\addplot[red, thick, domain=0.6:9.8] { (x/1.2) };
\addplot[green!60!black, thick, domain=0:10] {(0.35/(0.4*0.5))*x};
\legend{$\dot A{=}0$ (stylized), $\dot H{=}0$}
\end{axis}
\end{tikzpicture}
\caption{Phase portrait (illustrative). The green line is the $\dot H{=}0$ nullcline; the red curve approximates $\dot A{=}0$ with $R^*=\tfrac{\rho}{\sigma}H$. Trajectories inside the homeostatic zone spiral to equilibrium; outside, vectors tilt toward collapse.}
\end{figure}

% Figure 3: Lyapunov landscape (contours)
\begin{figure}[h]
\centering
\begin{tikzpicture}
\begin{axis}[
  width=12cm, height=8cm,
  view={0}{90}, colormap/viridis,
  xlabel={$A$}, ylabel={$H$},
  xmin=0, xmax=10, ymin=0, ymax=10]
\def\Astar{5.0}
\def\Hstar{6.0}
\addplot3[
  contour filled, samples=41, domain=0:10, y domain=0:10,
] {( (x-\Astar)^2 + 0.7*(y-\Hstar)^2 )/2};
\end{axis}
\end{tikzpicture}
\caption{Illustrative Lyapunov potential $V(A,H)=\tfrac12[(A-A^*)^2+0.7(H-H^*)^2]$. J-C-B steepens curvature (stronger restoring forces), widening the stable basin; removing repair (low $\lambda$) flattens the well.}
\end{figure}

\section{The Hierarchy-Extractive Archetype}
This worldview glorifies dominance and mistakes parasitism for strength.  
It assumes that inequality signals efficiency and empathy is weakness.  
Ecology refutes this: no mature ecosystem sustains dominance indefinitely; co-evolution and symbiosis drive persistence.  In repeated-game dynamics, reciprocity outperforms defection.  The archetype therefore represents a parameter regime—high α, low λ, inflated γ—that mathematically guarantees instability.

\begin{table}[h!]\centering
\caption{Archetype Claims vs Systemic Evidence}
\begin{tabular}{@{}lll@{}}\toprule
Claim & Counter-Evidence & Systemic Interpretation\\\midrule
Competition is sole driver & Co-evolution dominates & Cooperation widens basin\\
Inequality = efficiency & Correlates with fragility & Excess gradient → instability\\
Empathy = weakness & Enables coordination & Reduces entropy\\
Growth = vitality & Unbounded → overshoot & Needs negative feedback\\\bottomrule
\end{tabular}
\end{table}

\section{RGE / RCM + J-C-B as Stabilizers}
Justice internalizes costs (\(\alpha,\lambda\)); Cooperation couples host and repair (\(\beta,\rho\)); Balance limits damage and decay (\(\gamma,\sigma,\kappa\)).  These alter the Jacobian’s sign structure, ensuring negative trace and alternating determinant—mathematical homeostasis.

\begin{table}[h!]\centering
\caption{Ethical Axes as Control Parameters}
\begin{tabular}{@{}llll@{}}\toprule
Axis & Role & Mathematical Effect & Observable Proxy\\\midrule
Justice & Internalize costs & $-\partial A/\partial t$ damping & Repair/growth ratio\\
Cooperation & Regenerative coupling & $\uparrow\beta,\uparrow\rho$ & Diversity index\\
Balance & Limit overshoot & $\downarrow\gamma,\downarrow\sigma$ & Entropy export ratio\\\bottomrule
\end{tabular}
\end{table}

% Figure 4: J-C-B feedback loop triangle
\begin{figure}[h]
\centering
\begin{tikzpicture}[>=Latex, scale=1.05]
\tikzset{
  vrt/.style={circle, draw, thick, minimum width=11mm, align=center, fill=white},
  edg/.style={-Latex, thick},
  ann/.style={font=\footnotesize}
}
\node[vrt] (J) at (90:3.1) {Justice};
\node[vrt] (C) at (210:3.1) {Cooperation};
\node[vrt] (B) at (330:3.1) {Balance};

\draw[edg] (J) -- node[ann,sloped,above] {internalize externalities ($\downarrow\alpha$, $\uparrow\lambda$)} (C);
\draw[edg] (C) -- node[ann,sloped,above] {regenerative coupling ($\uparrow\beta,\uparrow\rho$)} (B);
\draw[edg] (B) -- node[ann,sloped,above] {overshoot limits ($\downarrow\gamma,\downarrow\sigma$, tune $\kappa$)} (J);

\node[align=center, font=\footnotesize, anchor=north] at (0,-3.9)
{Circulating stabilizer: each axis feeds the next, closing a damping loop that restores homeostasis.};
\end{tikzpicture}
\caption{The J–C–B triad as a circulating negative-feedback loop.}
\end{figure}

\section{Design Principles and Policy Prototypes}
\begin{table}[h!]\centering
\caption{Mechanisms and Model Effects}
\begin{tabular}{@{}llll@{}}\toprule
Mechanism & Function & Parameter & Example\\\midrule
Repair Budgets & Ensure regeneration & ↑ λ & Maintenance mandates\\
Entropy Taxes & Internalize externalities & ↓ α & Carbon/resource fees\\
Commons Dividends & Redistribute surplus & ↓ γ ↑ ρ & Public trusts\\
Co-op Incentives & Encourage mutualism & ↑ β ρ & Federated platforms\\
Circuit Breakers & Halt runaway loops & Adaptive γ(H) & Auto throttling\\\bottomrule
\end{tabular}
\end{table}

% Figure 5: Design flowchart
\begin{figure}[h]
\centering
\begin{tikzpicture}[node distance=9mm, >=Latex]
\tikzset{
  step/.style={draw, rounded corners, thick, align=center, minimum width=38mm, fill=gray!5},
  arr/.style={-Latex, thick}
}
\node[step] (detect) {Detect Runaway Signals\\($R/A\downarrow$, $E_{\text{out}}/E_{\text{in}}\uparrow$, $H\downarrow$)};
\node[step, right=22mm of detect] (choose) {Select Mechanism\\(entropy tax, repair budget, co-op incentive)};
\node[step, right=22mm of choose] (apply) {Apply Feedback\\($\downarrow\alpha$, $\uparrow\lambda$, $\uparrow\beta,\uparrow\rho$)};
\node[step, right=22mm of apply] (monitor) {Monitor Stability\\($\dot V<0$, basin width $\uparrow$)};

\draw[arr] (detect) -- (choose);
\draw[arr] (choose) -- (apply);
\draw[arr] (apply) -- (monitor);
\draw[arr] (monitor.south) .. controls +(0,-14mm) and +(0,-14mm) .. node[below,pos=0.5]{adaptive thresholds} (detect.south);
\caption{Policy/control flow: early detection $\rightarrow$ mechanism choice $\rightarrow$ parameter correction $\rightarrow$ stability monitoring (closed-loop).}
\end{tikzpicture}
\end{figure}

\section{Empirical and Simulation Program}
Empirical proxies: \(A\) = GDP; \(H\) = ecological + social health; \(R\) = repair spending.  
Falsifiable predictions: collapse when \(R/A<0.25\); cooperation density ↗ system half-life.  
Agent-based models test parameter sweeps over α, λ, β, ρ; stability region expands with J-C-B.  

% Figure 6: ABM schematic
\begin{figure}[h]
\centering
\begin{tikzpicture}[>=Latex, node distance=10mm]
\tikzset{
  agent/.style={draw, circle, minimum size=8mm, thick, fill=blue!7},
  env/.style={draw, rounded corners, thick, fill=green!6},
  pool/.style={draw, rounded corners, thick, fill=orange!10},
  arr/.style={-Latex, thick}
}
\node[env, minimum width=36mm, minimum height=12mm] (H) {Environment $H$};
\node[pool, right=40mm of H, minimum width=36mm, minimum height=12mm] (R) {Repair Pool $R$};

\node[agent, above=15mm of H] (f1) {};
\node[agent, below=15mm of H] (f2) {};
\node[agent, above right=10mm and 18mm of H] (f3) {};
\node[agent, below right=10mm and 18mm of H] (f4) {};
\draw[arr] (f1) -- node[above,sloped]{extract $\propto \alpha$} (H);
\draw[arr] (f2) -- (H);
\draw[arr] (H) -- node[above]{damage $\propto \gamma$} +(18mm,0);
\draw[arr] (R) -- node[above]{regenerate $\propto \beta$} (H);
\draw[arr] (f3) -- node[above,sloped]{invest $\lambda$} (R);
\draw[arr] (f4) -- (R);
\draw[thick, dashed] (f1) -- node[above]{coop} (f3);
\draw[thick, dashed] (f2) -- node[below]{coop} (f4);
\node[align=left, font=\footnotesize, anchor=north west, yshift=-2mm] at ($(R.south west)+(0,-8mm)$)
{Dashed links: cooperation $\Rightarrow$ $\uparrow\beta,\uparrow\rho$, $\downarrow\sigma$;\\
low $\lambda$ or broken links $\Rightarrow$ collapse risk.};
\caption{ABM wiring: agents extract from $H$, contribute to repair $R$, and form cooperative links that raise regeneration and resilience.}
\end{tikzpicture}
\end{figure}

\section{Counterarguments and Limitations}
Negative feedbacks may appear to hinder innovation, yet without them efficiency gains amplify entropy.  Measurement cost is real but shrinking via digital sensing.  Path dependence demands gradual transition.  Abstraction omits cultural delay effects; future work should include stochastic coupling.  The framework seeks persistence, not permanence—collapse and renewal remain part of recursive evolution.

\section{Conclusion}
Capitalism perfected replication but forgot repair.  The pathology is mechanical: feedback without damping.  The J-C-B triad supplies the minimal stabilizers—internalizing cost, coupling regeneration, and bounding extraction.  A civilization governed by these attractors would behave like an ecosystem: metabolic, self-repairing, enduring.  
Justice, Cooperation, and Balance are not virtues added to systems; they are the equations that let any recursion live.

\section*{References}
\begin{itemize}[leftmargin=1.5em]
\item Prigogine, I. \& Stengers, I. (1984). \emph{Order Out of Chaos.}
\item Schrödinger, E. (1944). \emph{What Is Life?}
\item Odum, H. T. (1971). \emph{Environment, Power and Society.}
\item Meadows, D. H. et al. (1972). \emph{The Limits to Growth.}
\item Georgescu-Roegen, N. (1971). \emph{The Entropy Law and the Economic Process.}
\item Ostrom, E. (1990). \emph{Governing the Commons.}
\item Holling, C. S. (1973). ``Resilience and Stability of Ecological Systems.'' \emph{Annual Review of Ecology and Systematics.}
\item Axelrod, R. (1984). \emph{The Evolution of Cooperation.}
\item Nowak, M. A. \& Sigmund, K. (1998). ``Evolution of Indirect Reciprocity.'' \emph{Nature.}
\item Daly, H. E. (1996). \emph{Beyond Growth.}
\item Rockström, J. et al. (2009). ``A Safe Operating Space for Humanity.'' \emph{Nature.}
\end{itemize}

\newpage
\section*{Lay Summary}
All living systems rely on feedback loops that balance growth with repair.  Human economies broke this law.  Capitalism behaves like a runaway loop that extracts faster than it restores.  Using the Recursive Generative Emergence framework, this paper models how \textbf{Justice, Cooperation, and Balance} act as mathematical stabilizers.  Embedding these principles in policy and design—repair budgets, commons governance, entropy taxes, adaptive algorithms—could realign civilization with the generative laws of nature.

\section*{Tweet-Length Teaser}
\emph{Capitalism is a runaway feedback loop that mistakes extraction for life. Using Recursive Generative Emergence, we show how Justice, Cooperation \& Balance restore homeostasis—and why nothing that refuses to repair itself can last.}

\end{document}