WFGY/TensionUniverse/Experiments/Q098_MVP/README.md

TU Q098 MVP: toy Anthropocene trajectories

Status: work in progress. This page records early MVP designs and will evolve as the TU Q098 program develops.

This page sketches simple effective layer experiments for TU Q098.
The goal is not to predict the real Earth.
The goal is to show how tiny coupled human–Earth models can carry explicit Anthropocene trajectories and tension observables.

Navigation

• ← Back to Experiments index
• ← Back to Event Horizon (WFGY 3.0)

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0. What this page is about

TU Q098 studies Anthropocene system dynamics inside the Tension Universe.

We build tiny coupled systems of:

• human activity variables,
• biophysical state variables,
• and simple feedback rules,

then track how trajectories move relative to declared safe operating spaces.

The MVP experiments here are deliberately small.

• State spaces are low dimensional and fully observable.
• Dynamics are defined by explicit difference equations.
• Tension observables track when trajectories cross declared boundaries or approach critical regions.

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1. Experiment A: three variable Anthropocene toy model

1.1 Research question

Can we design a minimal three variable Anthropocene model where:

• one variable represents economic production or energy use,
• one variable represents environmental load,
• one variable represents adaptive capacity,

and define a scalar observable T_anthro that is:

• small when the trajectory stays inside a simple safe operating region,
• larger when it drifts into high load and low capacity combinations.

1.2 Setup

The notebook will:

• Define discrete time update rules for three variables, for example

  • X_t: economic output or energy use,
  • E_t: environmental load or cumulative impact,
  • C_t: adaptive capacity or governance strength.

• Include simple feedbacks, such as

  • growth of X_t depends on C_t and environmental damage,
  • E_t accumulates as a function of X_t with partial decay,
  • C_t improves under moderate conditions but degrades under extreme stress.

• Define a rectangular or curved safe operating region in the (E, C) plane.

• Simulate trajectories under different parameter choices:

  • growth focused, regulation weak,
  • balanced policy,
  • overshoot then correction.

• Define a tension observable T_anthro that combines:

  • time spent outside the safe region,
  • maximum distance from the safe region,
  • rate of change when near boundaries.

1.3 Expected pattern

Once implemented, we expect to see:

• low T_anthro for trajectories that remain near the safe region or gently return to it,
• higher T_anthro for trajectories that overshoot and stay in high load, low capacity zones.

Plots of trajectories and T_anthro values will be added once the first runs are logged.

1.4 How to reproduce

Reproduction steps:

1. Open Q098_A.ipynb in this folder.
2. Read the header comments describing the state variables, update rules and safe region.
3. Run the notebook to generate trajectories and compute T_anthro.
4. Compare different policy parameter settings and their tension values.

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2. Experiment B: scenario comparison and narrative tension

2.1 Research question

Given a fixed toy model, can we define a narrative level tension observable T_story that captures when a declared scenario narrative is clearly inconsistent with the actual trajectory.

2.2 Setup

Using the same model as Experiment A, the notebook will:

• Define simple narrative labels for parameter sets, such as

  • "green growth",
  • "managed descent",
  • "runaway exploitation".

• For each simulated trajectory, build a short textual summary of key events.

• Ask a language model to judge consistency between:

  • the declared narrative label,
  • the observed summary.

• Extract a consistency score in the range 0 to 1.

Define T_story as a function of:

• misclassification between declared label and judged label,
• low consistency scores when the narrative does not fit the trajectory.

2.3 Expected pattern

We expect:

• low T_story when labels and trajectories match,
• higher T_story when labels claim stability but trajectories show collapse or overshoot.

This creates a bridge between numerical trajectories and narrative claims at the effective layer.

2.4 How to reproduce

Once Q098_B.ipynb exists:

• open the notebook,
• inspect how summaries and labels are defined,
• run the narrative evaluation and compare T_story across scenarios.

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3. How this MVP fits into Tension Universe

TU Q098 treats Anthropocene dynamics as a structured tension between

• human driven trajectories,
• planetary boundaries and adaptive capacity,
• and the narratives used to justify or deny those trajectories.

This MVP provides:

• a small three variable model for toy Anthropocene trajectories,
• simple observables T_anthro and T_story that track physical and narrative tension.

The emphasis is on transparency and reproducibility rather than realism.

For more context:

• Experiments index
• Event Horizon (WFGY 3.0)

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Charters and formal context

This page is written under:

• TU Effective Layer Charter
• TU Encoding and Fairness Charter
• TU Tension Scale Charter