diff --git a/TensionUniverse/Experiments/Q098_MVP/README.md b/TensionUniverse/Experiments/Q098_MVP/README.md new file mode 100644 index 00000000..bc1bad67 --- /dev/null +++ b/TensionUniverse/Experiments/Q098_MVP/README.md @@ -0,0 +1,193 @@ + + +# 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](../README.md) +- [← Back to Event Horizon (WFGY 3.0)](../../EventHorizon/README.md) + +--- + +## 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. + +--- + +## 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. + +--- + +## 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. + +--- + +## 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](../README.md) +- [Event Horizon (WFGY 3.0)](../../EventHorizon/README.md) + +--- + +### Charters and formal context + +This page is written under: + +- [TU Effective Layer Charter](../../Charters/TU_EFFECTIVE_LAYER_CHARTER.md) +- [TU Encoding and Fairness Charter](../../Charters/TU_ENCODING_AND_FAIRNESS_CHARTER.md) +- [TU Tension Scale Charter](../../Charters/TU_TENSION_SCALE_CHARTER.md)