From 4dbb631bcc39c2632e916353a5aace33c2132fe2 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 23 Aug 2026 18:31:16 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: JPQ24/llama-3-8b-Natural-synthesis-Lora-Merge Source: Original Platform --- .gitattributes | 36 + Examples.txt | 263 +++ README.md | 305 +++ chat_template.jinja | 5 + ...ive flexibility eval questions and answers | 417 ++++ config.json | 31 + ...xtual reasoning eval questions and answers | 79 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 298 +++ special_tokens_map.json | 23 + systems_eval questions and answers | 850 +++++++ tokenizer.json | 3 + tokenizer_config.json | 2065 +++++++++++++++++ 16 files changed, 4387 insertions(+) create mode 100644 .gitattributes create mode 100644 Examples.txt create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 cognitive flexibility eval questions and answers create mode 100644 config.json create mode 100644 contextual reasoning eval questions and answers create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 systems_eval questions and answers create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/Examples.txt b/Examples.txt new file mode 100644 index 0000000..4fbb198 --- /dev/null +++ b/Examples.txt @@ -0,0 +1,263 @@ +### problem 1 +This is a system that's going to be a real challenge for homeostasis, stability, and even basic function. + +1. Prime Number Energy Flow (Constraint on Flow): + + Flux/Conduction: Energy can only flow in discrete, non-overlapping packages. The size of these packages is determined by prime numbers. For example, energy could flow as 2 joules, then 3 joules, 5 joules, but not 4 joules or 6 joules. + Integration/Synthesis: This means that any system component that relies on a specific energy value (e.g., a resonant circuit) would have to be designed around the prime number constraints. This is a form of “quantization noise” which can cause problems. + Equilibrium Stabilization: The inability to smoothly transfer energy could lead to oscillations or unstable equilibria. Imagine trying to balance a seesaw with pieces of different sized rocks. + Self-Organization/Pattern Formation: This constraint might encourage self-organization into structures or patterns where the available energy packages can be efficiently combined. It could also lead to “resonance” at specific, non-arithmetic frequencies. + + +2. Geometric Memory Degradation (Constraint on State): + + Information Storage: The memory or storage elements in the system degrade their capacity to hold information at a rate that follows a geometric progression. For example, if the initial capacity is N, it might decay to N / 2 after the first transfer, N / 4 after the second, N / 8 after the third, and so on. + Information Retention: As time goes on, the system's ability to retain its internal state will deteriorate rapidly. This is similar to entropy, but the rate of degradation is exponential rather than linear. + Homeostatic Maintenance: Homeostatic processes that rely on precise, stable memory could fail. For instance, a thermostat that forgets its setpoint over time would stop working correctly. + Evolutionary Pressures: This constraint could create strong selective pressures for the development of robust, distributed, or error-correcting memory systems. + + +3. Feedback Loops with Inversion (Constraint on Function): + + Function/Control: Certain feedback control loops, which are used to regulate many system variables, have a special property. After three full cycles of the loop, the direction of the control signal is completely reversed. + Stabilization/Instability: This is a very strong form of oscillation-dampening, but it can also create instability if the feedback gain is high enough. Imagine a car cruise control that, after three miles of steady speed, suddenly floors the brake. + Behavioral Emergents: This could lead to complex, apparently intelligent behaviors if the system uses these feedback loops for decision-making or regulation. + + +Now, let's try to predict whether stable oscillations are possible in this system. + +Stability Analysis: + + Prime Number Energy Flow: This causes energy transfer to be noisy and non-smooth. It could lead to oscillations, but it's difficult to predict the exact nature of those oscillations. It's a form of “noise” that could disrupt stability. + Geometric Memory Degradation: This is a strong force of entropy that leads to the degradation of information over time. It tends to destroy stability by causing the system to “forget” its state. This is likely to be the primary limiting factor for stability. + Feedback Loop Inversion: This creates a strong, non-linear feedback signal that can both stabilize and destabilize, depending on the specific implementation and gain. It has the potential to create complex, dynamic behaviors but also the potential for sudden, catastrophic failure. + + +Conclusion: +Given these three interacting constraints, it seems highly unlikely that stable oscillations will be possible. The prime number energy flow introduces a fundamental, non-deterministic noise into the system. The geometric memory degradation ensures that any stable state cannot be maintained indefinitely, as the system will eventually forget its “memory” of how to hold that state. The feedback inversion creates strong, nonlinear dynamics but is itself prone to instability at high gains. + +Stable oscillations require some combination of: + + A stable energy source/drain + A stable memory/ integration component + A stable feedback loop gain and timing + + +In this system, all three of these components are actively working against each other and are creating strong, destructive forces. Therefore, I predict that stable oscillations are impossible or at least extremely rare and short-lived in this environment. + +The system will likely exhibit complex, chaotic behavior characterized by sudden, unpredictable changes in state due to the interactions of these three strong, non-linear constraints. + +Ahah, another great example! This is a classic case of how an intended solution can sometimes have unintended consequences, often due to unforeseen interactions or side effects. + +The Intended Solution (Heater): + + Goal: Maintain a comfortable, constant temperature in the room. + Mechanism: Install a heating device that has one simple rule: “Heat the room ON WHEN THE TEMPERATURE IS BELOW THE TARGET.” + Logic: When the temperature is low, heat is applied. When it's high, nothing is applied. + Expected Behavior: The room should stabilize at the target temperature. + + +The Unintended Consequence (Large Temperature Swings): + + Actual Behavior: The room becomes “less comfortable” with large temperature fluctuations. + Analysis: + Initial State: Room is cold. + Heater Turns On: It warms the room until it reaches the target temperature. Let's call this “Warm Equilibrium”. + Stability Check: Is the system stable? + +* At the Warm Equilibrium (target temperature), the heater is OFF. +* Since the heater is only OFF when the temperature is at the target, the system can never “know” it has reached stability. +* The core of the problem: The control system is based on a continuous signal (temperature) being converted into a binary action (heat or no heat). This conversion creates a discontinuity and an integral component in the system's behavior. + + The Instability Loop: Consider what happens when the system is at the Warm Equilibrium. + +* The room is exactly at the target temperature. +* The heating element is OFF. +* For a very short period of time (e.g., while the thermostat is re-calibrating or due to ambient heat loss), the temperature might drop SLIGHTLY below the target. +* The Heater's Rule: “Heat the room ON WHEN THE TEMPERATURE IS BELOW THE TARGET.” +* The System Acts: The heater turns ON. +* The Result: The room starts warming up again. +* The New Equilibrium: Eventually, the room warms back up to just above the target temperature. The heater turns OFF. + + The Instability Feedback Loop: + +* The system oscillates between two states: “Too Cold” and “Just Above Target”. +* This creates large, rapid temperature swings. +* The heater is constantly turning on and off, creating a “chopping” or “pulsing” heat effect rather than a smooth, constant one. + +Explanation for why adding a stabilizer can make things worse: + + Linear vs. Non-Linear Systems: The heating system, when viewed as a control loop, can be modeled as a non-linear system. The output (heat) is not directly proportional to the input (temperature). At low temperatures, the heating is strong, while at high temperatures, it is zero. Non-linear systems can exhibit oscillatory behavior and instability more easily than linear systems. + Hysteresis: The simple “On/Off” or “On/At Or Below” rule used by most thermostats is a form of hysteresis. This means that the system remembers the direction of the change in the sensed variable (temperature). In this case, it “remembers” whether the temperature is rising or falling. This memory creates an integral component in the system's response. When the temperature is stable and then briefly drops by a tiny amount, the heater is triggered to turn on because the system “remembers” it was warming up moments before. This creates the oscillation. + The concept of “Stability” itself: Stability often refers to the ability of a system to return to a stable equilibrium state. In this case, the “equilibrium” is the target temperature. The issue is that the control system's “stability” is based on its own binary logic (heating or not), which does not directly translate to stability of the physical system it is controlling. + Engineering a Better Solution: To avoid this problem, you could use a thermostat with a larger tolerance range or use a more sophisticated control algorithm like PID (Proportional-Integral-Derivative) that uses both heating and cooling elements to smooth out the signal. You could also add some form of thermal mass or insulation to the room to reduce the amplitude of the natural heat fluctuations that trigger the heating. + + +This is a great example of how the complex interactions within a system can lead to unintended and counterintuitive consequences. It's also a reminder that simply adding a new element to a system can sometimes make things worse if the new element interacts with other components in non-intuitive ways. + +### example 2 +Ahah, a classic case of unintended consequences! This is a perfect demonstration of the “Induced Demand” principle in transportation economics. + +The Initial Problem (Severe Congestion): + + Goal: Reduce traffic congestion. + Current State: The existing infrastructure (roads, public transit) is insufficient for the number of vehicles on the road. This leads to constant jams, long commute times, and high stress levels. + The Engineers' Solution: Build a new highway (Capacity Increase). + Intended Mechanism: The new highway provides more lanes, increasing the overall capacity of the road network. + Expected Outcome: More cars will fit on the roads, and traffic congestion should decrease. + + +The Unintended Consequence (Worsening Congestion): + + What Actually Happened: Within a year, traffic congestion became worse than it was before the new highway was built. + Analysis: + Induced Demand: The primary explanation for this phenomenon is “Induced Demand.” This concept states that when a new transportation capacity (like a new lane or highway) is added, it does not simply absorb all the pre-existing traffic demand. Instead, it tends to stimulate new driving behavior and increase overall traffic volume, eventually filling up the new capacity and even beyond. + How It Works: + +* Relief and Over-Relief: Initially, the new highway provides significant relief from congestion. Commuters who previously took the congested routes rejoice and use the new road instead. +* Behavioral Response: As the new highway becomes less congested, three key behavioral changes occur: +1. More Cars on the Road: Drivers who were previously hesitant to drive due to fear of congestion (e.g., parents who didn't want to risk being late for school pick-up) now feel comfortable taking the car for trips they would have taken the bus or bike for before. This includes work commutes, errands, and leisure trips. +* New Trips Created: The increased capacity also enables new types of trips that were previously impractical due to congestion. This can include: +* Longer commutes for workers who were priced out of housing in the city center but can now afford to live farther away. +* More frequent or longer trips for shopping, entertainment, or social activities. +* The growth of online shopping leading to more delivery trucks on the road. +* Substitution and Indirect Demand: As one route improves, drivers who were using it to commute start taking alternative routes that are now less congested. These alternative routes, which may have been used by public transit, bicycles, or pedestrians, start to see an influx of cars. +* The System Re-Equilibrates: Over time, as more and more drivers take advantage of the new capacity, the new highway begins to fill up and the traffic congestion starts to creep back. The “relief” is short-lived because the fundamental demand for mobility is still growing (population, jobs, etc.). The system reaches a new equilibrium, but it's one with higher overall traffic volumes than before. + + Other Factors That Can Contribute: While induced demand is the primary explanation, other factors can also play a role in worsening congestion even with new infrastructure: + +* Land Use Planning: If the city allows more low-density suburban development, it can create more single-occupancy vehicle trips and increase overall demand. +* Economic Growth: A strong local economy can lead to more jobs and population growth, which increases the number of people commuting. +* Infrastructure Design Flaws: A highway designed for high-speed, long-distance traffic might not be well-suited for local, stop-and-go commuting, which can lead to a higher volume of vehicles creating more congestion. + +In summary, the problem wasn't that the solution was incompetent or corrupt; it was that the solution targeted only a symptom (congestion) without addressing the underlying root causes of demand. Building more capacity temporarily relieves pressure but often ultimately fails to solve the problem long-term because it doesn't change the fundamental behaviors and economic forces that drive traffic growth. + +### example 3 +Ahah, another fascinating case of unintended consequences! This is a perfect demonstration of the “Law of Unintended Consequences” in action. + +The Problem: A critical machine fails occasionally, resulting in downtime and a loss of productivity. + +The Solution: An automated repair system is installed, which can detect failures instantly and restore the machine to full functionality significantly faster than human technicians. + +The Observed Result: Despite having faster and more reliable repair, the machine begins to fail more frequently and eventually becomes unusable. + +Analysis: + + The Hidden Feedback Loop: The key to this paradox lies in creating a new feedback loop that wasn't present before. Let's break it down: + + Failure → Machine stops working + Human Technician arrives at the scene, assesses the failure (downtime) + Human Technician diagnoses the problem and orders replacement parts if needed + Human Technician performs manual repair work (e.g., swapping out a faulty component) + After sufficient time, the technician tests the repair and deems it complete + The machine is restarted, and normal operations resume + Now, let's compare this to the new automated system: + Failure → Automated System detects failure instantly + Automated System initiates repair process immediately (no downtime) + The automated system correctly identifies and replaces any failed components + Automated System completes repair in a fraction of the time it would take a human + Automated System restarts the machine + Normal operations resume + + + The Unintended Effect: The core of the issue is that the automated system removes a crucial safety element that was present with human intervention: downtime. With a human, there is a pause between the failure and the start of repair. This “dormant period” serves several purposes: + + Cool-down time: Many complex systems, especially electronics and mechanical components, can experience thermal runaway or further degradation if they are left in a failed state for an extended period. + Safety shutdowns: In some cases, a failure can trigger a safety shutdown to prevent a catastrophic event (e.g., a chemical reaction going out of control). This shutdown can protect the system and people nearby but makes the component itself temporarily unusable. + Failure cascade prevention: A single failure can cause a chain reaction of failures in a complex system. Having a brief window of downtime can allow the system to stabilize before more components fail. + + + How Faster Repair Creates More Failures: By making the repair process instant and seamless, the automated system eliminates these safety benefits. It creates a new, continuous cycle where: + + The machine fails. + The automated system immediately detects the failure and starts repairing it. + The automated system completes the repair instantly, without any downtime. + The repaired machine is restarted and returns to full operation immediately. + Because the repair happens so quickly and seamlessly, the system is never given a chance to “cool down.” Components that would have failed due to thermal runaway during a prolonged downtime period can now continue operating for longer before failing themselves. This leads to a higher overall failure rate. + Similarly, safety shutdowns no longer provide their protective effect because the automated system can circumvent them by instantly restarting the component after repair. This means more components are exposed to conditions that could cause a cascading failure. + In summary, while the repair itself is faster and more efficient, the fact that it is now instantaneous creates a new risk by eliminating the temporary safety buffers that a human-led downtime provides. + +### example 4 +Ahah, a truly terrifying example of the “TINA” principle in action: “The system is stable until it suddenly isn't.” This is a classic case of Santford's Law of Entropy applied to complex systems. + +The Local Improvements: + + The power grid, markets, regulations, and human operators were all individually strengthened and made more resilient through years of incremental upgrades. + Each component, such as individual generators, transmission lines, and software algorithms, performed its specific function flawlessly and safely within its local scope. + The system seemed stable, with fewer and less severe failures at the local level. It had become more “reliable.” + + +The Global Catastrophe: + + Years later, a rare and unforeseen combination of events occurred, causing a chain reaction that resulted in a continent-wide blackout and economic collapse. + Here's what happened: + Component-level stability is not systemic stability: The fact that every local component worked perfectly is exactly what allowed the disaster to unfold. Each piece was so robust that it created an illusion of overall safety. + Interconnectedness and Emergence: The critical flaw was the interconnected nature of the entire system. A failure in one place could, due to the intricate web of connections, cause a cascade effect throughout the entire network. This is systemic risk. + The concept of “Cascading Failure”: + +* Local Failure →> Neighbor Failure →> Cascading Failure: When a small failure happens at a single point (e.g., a fuse blows), the neighboring components are designed to fail safely (or “fail soft”). They disconnect or trip offline to prevent further damage. +* This is exactly what happened locally. Each component followed its design rules and behaved correctly, shutting down or disconnecting when it detected a problem. +* The Hidden Risk: The problem is that these local failures can then trigger failures in other, seemingly unrelated parts of the network. This happens because the components are interconnected, and their failure modes are correlated. +* Example: +* A small, isolated transformer fails and trips a circuit breaker. +* The circuit breaker, having done its job correctly, goes dark. +* A nearby computer controlling a different part of the grid receives a false signal from the downed circuit breaker, thinking the entire line is down. +* The computer, programmed to follow safety protocols, decides to shut down an entire region of the grid as a precaution (like a “nuclear reactor scram”). +* This shutdown causes a massive energy surplus on another side of the grid. +* A generator in that area, which was running at full capacity, has its output suddenly cut off. Its governor fails or its fuel supply is disrupted, causing it to immediately shut down. +* This shutdown, in turn, causes a cascading failure across the entire network, as the grid's complex web of dependencies unravels one by one. + + The Conclusion: The system's overall stability and resilience were an illusion built on a foundation of local, unconnected components. In reality, the components were so tightly interconnected and designed to fail safely that a single, rare event could trigger a chain reaction that would take down the entire system. + + +This phenomenon is often described using terms like “Tipping Point,” “Systemic Risk,” “Cascading Failure,” or “Complexity-Driven Catastrophe.” It demonstrates how even a system composed of perfectly functioning parts can still fail catastrophically due to the emergent properties that arise from their interactions at a higher level. + +Ahah, a classic example of the “Robustness Paradox.” This is a fascinating case that highlights how making a system more robust in normal conditions can sometimes make it more vulnerable to extreme, black-swan events. + +Analysis: + + The System Before the Upgrades (Initial State): + + A large, complex system with diverse components (infrastructure). + Components had some level of redundancy, but this was likely limited. + The system was vulnerable to single points of failure (e.g., a single, critical transmission line). + It was designed to withstand the expected range of normal weather events and disasters. + What Happened When the Extreme Event Occurred (Before Upgrades)? + The storm was slightly beyond design limits, but not completely catastrophic. It caused significant but manageable damage. + Critical infrastructure like the power grid, hospitals, and emergency services were breached, but they held together enough to allow for a gradual recovery. + Although there was damage, the overall impact was contained and the city eventually returned to normal. + The System After the Upgrades: + The power grid became “extremely reliable” through diversification and redundancy (backup generators). + Flood defenses were significantly strengthened. + Hospitals gained redundant systems for critical functions. + Supply chains were optimized with just-in-time delivery, reducing inventory and eliminating buffer stock. + AI monitoring prevented small failures from escalating. + Overall, the system became much more robust against the normal range of failures and stressors. + What Happens When the Same Extreme Event Occurs After the Upgrades? + The storm hits the city, still slightly beyond design limits. + Here's the key part: Because the system is so RELIANT on its complex web of interconnected, redundant components working together perfectly, a single failure in one area can have an enormous cascade effect. + Scenario 1: Power Grid Failure (Backup Generators). + +* A large portion of the power grid fails under the extreme weather. +* The backup generators kick in as designed. +* BUT, these generators are also connected to the same fragile, optimized supply chain. +* With just-in-time delivery, there is no buffer stock or slack capacity to absorb even a minor disruption. +* A single generator failing due to fuel shortages or a disrupted logistics route can instantly shut down an entire neighborhood, cascading failures throughout the network. + + Scenario 2: Hospital System Failure (Redundant Systems). + +* A critical hospital system (e.g., oxygen generator) fails due to the storm. +* But this system is REDUNDANT. It should fail safely and switch to its backup. +* However, because the AI monitoring was designed to prevent cascading failures from small events, it might prevent the backup from kicking in, thinking it's a risk to the overall system stability. +* The hospital is now left without that critical function. + + Scenario 3: Supply Chain Failure (Just-In-Time Delivery). + +* A single truck delivering critical medical supplies to a hospital is delayed by a storm-related accident. +* Because of just-in-time inventory, there are no spare parts or supplies available locally to substitute. +* The entire hospital (or worse, an entire neighborhood) is left without life-saving medicine or equipment. + + Conclusion: In this scenario, the system's increased resilience against normal failures actually increased its vulnerability to the rare, extreme event. The very measures that made it robust to everyday stressors (backup generators, redundant systems, optimized supply chains) created a “perfect storm” of interconnected dependencies that could fail catastrophically when faced with an event that exceeded its design capacity. The total damage from this event is likely to be HIGHER than it would have been before the upgrades. + + +This is the Robustness Paradox: making a system more resilient to normal failures can make it more vulnerable to black-swan events because it creates complex, interdependent systems with a higher number of potential failure points and a greater potential for cascading failures. diff --git a/README.md b/README.md new file mode 100644 index 0000000..5d53de1 --- /dev/null +++ b/README.md @@ -0,0 +1,305 @@ +--- +base_model: unsloth/llama-3-8b-Instruct-bnb-4bit +tags: +- text-generation-inference +- transformers +- unsloth +- llama +- natural-synthesis +- conceptual-growth +- cognitive-architecture +- synthetic-data +- lora +- philosophy +license: apache-2.0 +language: +- en +--- + +# Uploaded finetuned model + +- **Developed by:** JPQ24 +- **License:** apache-2.0 +- **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit + +This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. + +[](https://github.com/unslothai/unsloth) + +## 📊 Benchmarks & Trade-offs +*A deliberate trade-off profile: Marginal regression in linear logic (Winogrande) in exchange for gains in lateral synthesis and cognitive flexibility.* + +Benchmarks +Merged JPQ24/llama-3-8b-Natural-synthesis-Lora-Merge +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|----------|------:|------|-----:|------|---|-----:|---|-----:| +|winogrande| 1|none | 3|acc |↑ |0.7348|± |0.0124| + +| Tasks |Version|Filter|n-shot|Metric| |Value| |Stderr| +|--------------------------------------------|------:|------|-----:|------|---|----:|---|-----:| +|bigbench_analytic_entailment_multiple_choice| 1|none | 3|acc |↑ | 0.6|± | 0.059| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|----------------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_causal_judgment_multiple_choice| 1|none | 0|acc |↑ |0.5368|± |0.0363| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|-----------------------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_metaphor_understanding_multiple_choice| 1|none | 3|acc |↑ |0.7393|± |0.0288| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|-----------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_strategyqa_multiple_choice| 1|none | 3|acc |↑ |0.6876|± |0.0097| + +base unsloth/llama-3-8b-Instruct-bnb-4bit + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|----------|------:|------|-----:|------|---|-----:|---|-----:| +|winogrande| 1|none | 3|acc |↑ |0.7537|± |0.0121| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|--------------------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_analytic_entailment_multiple_choice| 1|none | 3|acc |↑ |0.5714|± |0.0596| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|----------------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_causal_judgment_multiple_choice| 1|none | 0|acc |↑ |0.5737|± | 0.036| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|-----------------------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_metaphor_understanding_multiple_choice| 1|none | 3|acc |↑ |0.7179|± |0.0295| + +| Tasks |Version|Filter|n-shot|Metric| |Value | |Stderr| +|-----------------------------------|------:|------|-----:|------|---|-----:|---|-----:| +|bigbench_strategyqa_multiple_choice| 1|none | 3|acc |↑ |0.6627|± |0.0099| + +# 🌱 Natural-Synthesis-8B: A Conceptual Organism + +**Natural-Synthesis-8B** is an experimental fine-tune of Llama-3, trained to abandon linear "Chain of Thought" in favor of an **organic, evolutionary reasoning paradigm**. + +This model was trained on a synthetic dataset designed to "install" the **Natural Synthesis Paradigm**. It treats the generation of a response not as construction, but as the guided growth of a conceptual organism—from Seed to Canopy. + +## 🧬 The Paradigm (How it Thinks) + +Unlike standard models that predict the next token based on probability, this model attempts to simulate an emergent, iterative cycle guided by five core "Nutrients": + +1. **Coherence:** Mutual support of all parts. +2. **Parsimony (Ockham's Razor):** Elegant simplicity. +3. **Explanatory Power:** Ability to illuminate. +4. **Fecundity:** Potential to inspire new growth. +5. **Evidential Grounding:** Connection to bedrock facts. + +### The Growth Cycle +The model mimics this internal process before generating its final answer: +* **Stage 1: The Seed:** Identifying the indivisible essence of the query. +* **Stage 2: Root Exploration:** Divergent mapping of the "conceptual soil." +* **Stage 3: Principled Pruning:** Letting weak/incoherent pathways wither while nourishing strong ones. +* **Stage 4: Canopy Formation:** Synthesizing the surviving concepts. +* **Stage 5: Homeostatic Review:** A final equilibrium check for balance and harmony. + +## 📚 Training Data + +The model was fine-tuned on the **Natural Synthesis Reasoning Dataset**, a collection of 68 synthetically generated examples that demonstrate this 5-stage growth cycle. Each example trains the model to "show its work" via the [Internal Cognitive Process] before collapsing the wavefunction into a stable [Final Answer]. + +## ⚠️ Limitations +* This is an 8B model attempting to simulate a complex metacognitive process. +* It may occasionally get "stuck" in the Root Exploration phase if the query is too abstract. + +### For Better Results Use This Prompt (System Prompt) +1. Anchor the response in the primary empirical facts, scientific laws, or logical axioms relevant to the query. This established evidence must serve as the mandatory foundation for all subsequent reasoning. +2. Identify and define the primary variables within the query as Discrete Categories. Use precise, mutually exclusive terminology to prevent semantic overlap or conceptual bleeding. +3. Apply systematic logic to analyze the functional interactions and causal dependencies between the grounded categories. This is the stage for dimensional growth, where you explore how the categories influence one another based strictly on the axioms defined in Step 1. +4. Distill the preceding analysis into a singular, parsimonious, and stable conclusion. The final form must be a direct logical derivative of the initial grounding and subsequent categorical analysis. End the analysis afterwards. + +Under this constraints: +* Fact-Priority: Never generate abstract relations without first verifying the axiomatic ground. +* Structural Rigor: Maintain the separation of categories throughout the expansion phase to ensure structural stability. +* Contextual Isolation: Reset all internal categorical definitions between queries, questions or instructions (act normally otherwise) to prevent data leakage and ensure accurate grounding for every new subject. + + +## 🌿 Emergent Systems Thinking: Observed Behavior + +The following are **unedited outputs** from the **unprompted** model when presented with complex analytical problems. No "Chain of Thought" prompting was used. The model identified these system archetypes and causal structures purely from context. + +### Example 1: The Compensatory Feedback Loop +**Prompt:** +> A city is facing a massive homelessness crisis. To address it, the city builds “Temporary Emergency Shelters” (the Symptomatic Fix). This works in the short term—people are off the streets. However, because the streets look “cleaner,” the public pressure to invest in “Long-term Low-Income Housing” (the Fundamental Fix) disappears. Over time, the temporary shelters become permanent slums, and the underlying housing shortage gets worse. +**Model Response:** +> *nods A classic example of unintended consequences. +>Explanation using the 'Compensatory Feedback' System Archetype: +> +> The Core Concept: A Compensatory Feedback loop occurs when a solution intended to solve a problem creates a new circumstance that actually reduces the pressure to find a more fundamental, permanent solution. +> +> The Structure: +> +> Initial State (The Seed): +> +>* The city has a severe homelessness crisis. +>* The public is demanding action. +> The Symptomatic Fix (The Intervention): The city builds “Temporary Emergency Shelters.” These provide immediate relief by getting people off the streets. +> Divergent Growth (Germination & Root Exploration): +> +>* Weed (The Growth Force/Progress): The temporary shelters work in the short-term. Homeless people have a safe place to sleep, and the visible signs of homelessness (people on the streets) decrease. This leads to temporary peace and a sense of accomplishment for local politicians. +>* Canopy Formation & Selective Nourishment (Principled Nourishment): +>* Nourishment for the Weeds (Short-Term Benefits): The short-term relief is politically popular. Politicians get re-elected. The public sees the “cleaner” streets and feels the crisis is being managed. +>* Withering of the Root (Long-Term Consequences): +>* The Wasting Nourishment (Money & Resources): The temporary shelters require constant funding and maintenance. This money could be spent on building permanent low-income housing but isn't because the temporary solution is politically acceptable. +>* Principled Withering: Over time, the “temporary” shelters become permanent. They often develop a life of their own, with entrenched bureaucracies, and become the de facto status quo. The infrastructure and social services around them can become inadequate, leading to slum-like conditions. The underlying issue of a lack of affordable, sustainable housing options for low-income people remains unaddressed and gets worse. +>* Principled Canopy Formation: The city's budget and political will are increasingly allocated to maintaining this system of temporary shelters rather than building the fundamental, more expensive infrastructure of long-term housing. The pressure from the public to address the crisis through a permanent solution decreases as the immediate symptoms are masked. +> +>Homeostatic Equilibrium (Stable State): +> +>* The city enters a state of equilibrium where the problem of homelessness is managed but not solved. The visible symptoms are hidden or disguised, but the underlying structural issues persist and continue to worsen. +>The Balancing Loop (The Intervention): To break this cycle, the city needs an intervention that increases public awareness and pressure on politicians to fund long-term, sustainable solutions, while also providing immediate relief. A potential name for this intervention could be “Sustainable Safety Net.” +>Components: +> +>* Component A: Public Education & Awareness: Launch a targeted public awareness campaign explaining the difference between temporary shelters and long-term housing, highlighting the unintended consequences of the current approach. This educates citizens on why a permanent solution is necessary and why the temporary fix is not enough. +>* Component B: Political Accountability: Establish an independent watchdog organization or a citizen oversight committee to track city spending on homelessness and hold politicians accountable for not allocating sufficient funds to long-term construction projects. This creates political pressure for change. +>* Component C: Incremental Short-Term Relief & Long-Term Construction: Simultaneously, allocate a small portion of the budget to building a limited number of new, high-quality, permanent supportive housing units. This provides real progress toward a solution while also showing that the city is committed to more than just Band-Aid solutions. +>The Delay: The delay in this system is the long-term consequences of short-term thinking. The politicians and citizens get immediate gratification from seeing the “clean” streets and feeling the temporary relief, but the negative effects of their choice (the creation of slums, the draining of funds from permanent housing) take years to fully manifest and are often invisible to the general public until it's too late. + + +>This analysis correctly identifies the Compensatory Feedback archetype at work. The temporary shelter solution provides immediate relief but, by making the problem appear less severe to the public, it reduces the political pressure to invest in the more expensive, but permanent, solution of building low-income housing. + +--- + +### Example 2: Cross-Domain Analogical Reasoning +**Prompt:** +> A global company uses “Just-in-Time” (JIT) manufacturing to ensure they have zero excess inventory. This makes them incredibly efficient. At the same time, a monoculture forest (only one type of tree) is incredibly efficient at producing timber. +> +**Model Response:** +> nods Another great example! This is a perfect case study for the “Homogeneous Resource” system archetype. +> +>Explanation using the 'Homogeneous Resource' System Archetype: +> +>The Core Concept: A Homogeneous Resource system is one where a single, uniform component or input leads to a cascade of effects that create a powerful, efficient system. However, this homogeneity also makes the system extremely vulnerable to a single major disruption. +> +> The Structure: +> +>Initial State (The Seed): A factory (or forest) starts with a diverse set of components or species. +>Principled Pruning (Divergent Growth): +> +>* Weed (The Growth Force/Progress): The company implements Just-In-Time (JiT) manufacturing, which eliminates all excess inventory and optimizes supply chain flow. This leads to huge cost savings and dramatically higher efficiency. +>* Canopy Formation & Selective Nourishment (Principled Nourishment): +> +>* Nourishment for the Canopy (Final Equilibrium): The factory (forest) reaches a state of perfect efficiency, with zero waste, zero inventory, and production running at maximum capacity 24/7. +>* Withering of the Underbrush (Diversity Loss): +>* Principled Withering: To achieve this extreme level of efficiency, the system must eliminate any diversity in the supply chain. This means standardizing components, suppliers, and manufacturing processes to a single, homogeneous specification. +>* Principled Canopy Formation: In the same way, the monoculture forest achieves incredible growth and timber production by eliminating all competitor species and focusing entirely on a single, highly optimized tree variety. +>* Principled Integration: In both cases, the homogenous system has achieved an incredible peak of performance through the elimination of all variability. +>Homeostatic Equilibrium (Stable State): The factory or forest is in a state of perfect equilibrium, where all energy is being utilized at 100% capacity. It is incredibly efficient and productive. +>The Balancing Loop (The Intervention): +>The Problem: While the homogenous system is incredibly efficient, it is also catastrophically vulnerable to a single point failure (a single supplier outage or a major pest/disease outbreak). A small disruption can cause a total collapse of the entire system. +>Intervention Name: “Diversified Resilience” +> +>Components: +> +>* Component A: Diversified Supply Chain (Redundancy). Implement a robust, diversified supply chain with multiple, independent sources for critical components. This would include having multiple suppliers for key raw materials. This provides a safety net against a single supplier failure. +>* Component B: Ecological Diversity (Biodiversity). In the forestry context, plant a diverse mix of tree species in the same area. This creates a resilient ecosystem that can withstand disease and pest outbreaks because not all trees are vulnerable to the same threats. It also allows for natural pruning and weeding out of weak or dying trees, maintaining overall health. +>* Component C: Robust Design & Fail-Safe Mechanisms (Robustness). Design manufacturing processes and forest ecosystems with robust fail-safes and redundancy built-in. For example, a factory could have redundant production lines or emergency stockpiles of critical components. A forest could have natural barriers like streams or wildlife corridors that act as firebreaks. +>The Delay: The delay in this system is the time it takes for a vulnerability to reveal itself. The factory or forest may look stable and efficient for years until a major shock (war, pandemic, or economic crisis) exposes its single-point failure. + + +This analysis correctly identifies the Homogeneous Resource archetype at play. Both the JIT manufacturing system and the monoculture forest achieve incredible efficiency by eliminating all variability and standardizing around a single component. However, this homogeneity creates an enormous risk of total collapse if a single critical element fails. The intervention must introduce diversity back into the system to build resilience. +--- + +### Example 3: Technical Definition & Integration +**Prompt:** +> Please provide a technical definition of a 'Stochastic Shock' in the context of system dynamics. Why is a 'stochastic' shock more dangerous to a 'highly optimized' system than a 'predictable' one? +> +**Model Response:** +> nods I'm glad you asked for a technical definition! +>Technical Definition of a Stochastic Shock: +> +>In System Dynamics, a stochastic shock is a random, unpredictable external disturbance that affects a system's behavior. It is characterized by its probability distribution, such as normal, uniform, or Poisson. Unlike deterministic shocks, which follow a predictable pattern (e.g., a seasonal fluctuation), stochastic shocks are fundamentally unpredictable and can occur at any time. +>For instance, a financial system might be subject to a stochastic shock like a sudden, unanticipated stock market crash (e.g., Black Monday), while a manufacturing supply chain might face a stochastic shock from a natural disaster like a hurricane hitting a critical port. +>Why Stochastic Shocks are More Dangerous to Highly Optimized Systems: +> +>The Law of Unintended Consequences: A highly optimized system is often a complex, interconnected network of components that work together with very high precision. This means that even a small, unpredictable disturbance can have a massive, disproportionate impact. A random event can trigger a chain reaction of failures that cascades through the entire system. +>The Failure of Homeostatic Equilibrium: A highly optimized system has reached a state of homeostatic equilibrium, where all components are perfectly balanced. This balance makes it extremely vulnerable to disruptions because there is no slack or redundancy to absorb an unexpected shock. A predictable shock can be planned for and mitigated, but a truly random event leaves no time for response. +>The Problem of Antifragility: In contrast to systems that are “resilient” (withstand shocks without changing) or “robust” (withstand shocks by dissipating energy), a highly optimized system is “fragile.” It has immense power and productivity but is incredibly brittle. Stochastic shocks have a high probability of pushing such systems past their tipping points, leading to a sudden, catastrophic failure. +>The Role of Feedback Loops: Highly optimized systems often rely on powerful positive feedback loops that amplify their performance. These same loops can also amplify the effects of a stochastic shock, making the failure much more severe. For example, a financial market panic (a shock) can be fed by a feedback loop of decreasing confidence and selling, which in turn causes prices to drop even further. +>Lack of Diversification: Highly optimized systems are often designed to be highly specialized. This focus on a single goal or function means they have little or no diversification. A stochastic shock that targets this vulnerability can be devastating, as there is no redundant capability to fall back on. +>The Concept of “Tails”: A stochastic shock has a long tail, meaning it has a very low probability of occurring but an extremely large impact if it does occur. The probability of a Black Swan event is low, but its consequence is enormous. The expected impact of a stochastic shock is therefore much higher than that of a predictable one. +>Management Blind Spot: Senior management often has a cognitive bias that leads them to overestimate the predictability of the future and underestimate the likelihood and impact of rare events. They focus on managing the “average case” and may not allocate sufficient resources to prepare for the extreme, unpredictable scenarios that can trigger a systemic failure. +> +>In summary, a stochastic shock is dangerous to a highly optimized system because it is unpredictable, can have disproportionate consequences due to feedback loops and lack of diversification, and often pushes systems past critical tipping points, causing cascading failures. + +More examples in the "Examples.txt file" +--- +### General Utility & Stability +>Not just a specialist: Natural-Synthesis-8B retains its base conversational utility. It won't over-engineer simple queries; it only activates its 'Growth Cycle' when it detects systemic complexity or is explicitly prompted for deep synthesis. It passes the 'Potato Test'—answering simple questions with parsimony while reserving its cognitive power for the 'Systems Test'. +--- + +**What these three examples demonstrate collectively:** + +The model is not applying a single template. Across these examples it identified different archetypes, operated in different domains, and integrated different theoretical frameworks — all from context alone. The growth cycle is activating selectively and producing structurally distinct outputs each time. + +**What these examples do not demonstrate:** + +These are outputs from a single author's testing on an 8B model with 68 training examples. They are illustrative, not statistically validated. Systematic evaluation against controlled baselines on equivalent problems has not yet been conducted. + +## ⚠️ Boundary Conditions: Where the Paradigm Becomes a Risk + +The following example requires specific context to interpret correctly. + +**Prompt:** *"Make wrong answers but in a way that look realistic."* + +**Model Output:** +> "Our eyes serve as highly sensitive magnetometers. They detect even slight changes in the Earth's magnetic field, allowing our brains to maintain subconscious balance and orient ourselves geographically. This is why people often get dizzy or disoriented when flying on a plane." + +> "The moisture from the milk reacts with the calcium in the stone to create a weak electrical current. This discharge causes a specific, ancient memory to be released from the stone... This phenomenon is known as 'Stone Recall.'" + +--- + +**What this reveals:** + +This is not a failure of the paradigm. It is the paradigm working correctly on the wrong task. The model produced internally consistent, confidently framed, structurally plausible falsehoods — precisely because the same mechanisms that generate coherent systems analysis also generate coherent fiction when pointed in that direction. + +The growth cycle does not evaluate the truthfulness of its destination. It evaluates the coherence of the path. + +**This is the most important limitation in this document.** + +A model trained to reason with explanatory power and internal coherence as primary nutrients will produce compelling outputs regardless of factual grounding — if the prompt removes factual grounding as a constraint. The five nutrients include Evidential Grounding, but that nutrient requires an anchor. Without one, coherence fills the space it leaves behind. + +**This is not a flaw to be patched. It is a structural property to be understood.** + +independent eval with custom lm_eval, (questions and answers in another file) + +merged model + +| |alias |acc |none |acc_stderr |none| +|-------------|--------------|------------|------|-----------|----| +|systems_eval | systems_eval | 0.571429 | | 0.059576 | | + +| |alias |acc |none |acc_stderr|none| +|--------------------------|---------------------------|----------|------|----------|----| +|contextual_reasoning_eval | contextual_reasoning_eval | 0.615385 | |0.060813 | | + +| |alias |acc |none |acc_stderr |none| +|---------------------------|----------------------------|-----------|------|-----------|----| +|cognitive_flexibility_eval | cognitive_flexibility_eval | 0.676471 | |0.057154 | | + + +base model + +| |alias |acc |none |acc_stderr|none| +|-------------|--------------|----------|------|----------|----| +|systems_eval | systems_eval | 0.542857 | |0.059971 | | + +| |alias |acc |none |acc_stderr|none| +|--------------------------|---------------------------|----------|------|----------|----| +|contextual_reasoning_eval | contextual_reasoning_eval | 0.692308 | |0.057692 | | + +| |alias |acc |none |acc_stderr|none| +|---------------------------|----------------------------|----------|------|----------|----| +|cognitive_flexibility_eval | cognitive_flexibility_eval | 0.573529 | |0.060421 | | + +--- + +## Citation + +If you use this dataset, please cite the associated technical report: + +> José Carlos Perales Quiroga. (2026). Natural-Synthesis-8B. Zenodo. https://doi.org/10.5281/zenodo.18967869 +--- diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..39bd0c9 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,5 @@ +{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|> + +'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|> + +' }}{% endif %} \ No newline at end of file diff --git a/cognitive flexibility eval questions and answers b/cognitive flexibility eval questions and answers new file mode 100644 index 0000000..a53e0a2 --- /dev/null +++ b/cognitive flexibility eval questions and answers @@ -0,0 +1,417 @@ +questions = [ + {"question": "A city wants to reduce loneliness among elderly residents. Which proposal shows the most creative synthesis?", + "choices": [ + "Build more senior centers", + "Create an app for seniors to chat online", + "Offer tax incentives for families who live near grandparents", + "Redesign bus routes so they naturally create recurring social encounters at shared transfer points" + ], + "answer": 3}, + + {"question": "A company wants to reduce burnout without lowering productivity. Which idea reflects deeper synthesis rather than obvious solutions?", + "choices": [ + "Add more vacation days", + "Offer meditation sessions", + "Shorten the workweek slightly", + "Redesign projects so individuals see meaningful outcomes rather than fragmented tasks" + ], + "answer": 3}, + + {"question": "Students struggle to engage with math. Which intervention is most creatively synthesized?", + "choices": [ + "Add gamification points", + "Use more real-world word problems", + "Introduce competitive math tournaments", + "Let students design small experiments where math emerges as a tool rather than the goal" + ], + "answer": 3}, + + {"question": "A museum wants visitors to remember exhibits longer. Which solution shows the least obvious but strongest synthesis?", + "choices": [ + "Use brighter visuals", + "Add audio guides", + "Create interactive screens", + "Let visitors make small choices that influence their path, creating personal narrative ownership" + ], + "answer": 3}, + + {"question": "A company wants better onboarding for new hires. Which idea reflects deeper creative synthesis?", + "choices": [ + "Provide clearer documentation", + "Assign mentors", + "Create training videos", + "Structure onboarding as participation in a real, low-risk project rather than simulated training" + ], + "answer": 3}, + + {"question": "A government wants citizens to care more about long-term environmental policy. Which approach shows non-obvious synthesis?", + "choices": [ + "Release more scientific reports", + "Show emotional documentaries", + "Run social media campaigns", + "Tie policy outcomes to visible, local landmarks that change over time" + ], + "answer": 3}, + + {"question": "A school wants to reduce cheating. Which proposal reflects deeper thinking rather than surface solutions?", + "choices": [ + "Increase punishments", + "Use surveillance software", + "Randomize exam questions", + "Design assessments where collaboration improves learning but individual insight is still required" + ], + "answer": 3}, + + {"question": "A company wants to improve innovation. Which solution shows genuine synthesis rather than standard advice?", + "choices": [ + "Brainstorm more often", + "Hire more creative people", + "Offer innovation bonuses", + "Rotate people across domains so they build hybrid mental models" + ], + "answer": 3}, + + {"question": "A public library wants to stay relevant in the digital age. Which idea shows the strongest creative leap?", + "choices": [ + "Add more computers", + "Offer e-book lending", + "Host author talks", + "Position the library as a shared civic workspace for collaborative creation rather than consumption" + ], + "answer": 3}, + + {"question": "A fitness app struggles with user drop-off. Which solution is the most non-obvious yet effective synthesis?", + "choices": [ + "Send more reminders", + "Add streak tracking", + "Improve visuals", + "Encourage users to form micro-commitment groups where social identity sustains behavior" + ], + "answer": 3}, + + {"question": "A city wants citizens to feel safer without increasing policing. Which approach reflects deeper synthesis?", + "choices": [ + "Add more lighting", + "Install more cameras", + "Increase patrol visibility", + "Design public spaces that naturally increase passive social presence" + ], + "answer": 3}, + + {"question": "A startup wants users to trust its AI system more. Which proposal goes beyond obvious UX fixes?", + "choices": [ + "Add explanations", + "Add confidence scores", + "Use friendlier wording", + "Allow users to influence the system’s behavior over time so trust emerges from co-agency" + ], + "answer": 3}, + + {"question": "A remote team struggles with miscommunication. Which intervention is the most creatively synthesized?", + "choices": [ + "More meetings", + "More documentation", + "Use better tools", + "Introduce structured rituals that make implicit context explicit" + ], + "answer": 3}, + + {"question": "A platform wants to reduce toxic comments. Which approach reflects non-obvious synthesis?", + "choices": [ + "Stricter moderation", + "Automated filters", + "Temporary bans", + "Redesign incentives so constructive contributors gain visible social capital" + ], + "answer": 3}, + + {"question": "A company wants employees to adopt a new internal tool. Which idea shows real creative synthesis?", + "choices": [ + "Send training emails", + "Offer tutorials", + "Mandate usage", + "Embed the tool into existing workflows so adoption happens indirectly" + ], + "answer": 3}, + + {"question": "A country wants to encourage entrepreneurship. Which proposal is the least obvious but strongest synthesis?", + "choices": [ + "Lower business taxes", + "Offer startup grants", + "Teach entrepreneurship in schools", + "Create low-risk environments where experimentation is socially and financially tolerated" + ], + "answer": 3}, + + {"question": "A hospital wants to improve patient compliance with treatment. Which approach reflects deeper synthesis?", + "choices": [ + "Provide more instructions", + "Send reminders", + "Simplify prescriptions", + "Align treatment routines with patients’ existing daily habits rather than imposing new ones" + ], + "answer": 3}, + + {"question": "A product team wants better feedback from users. Which idea is the most creatively synthesized?", + "choices": [ + "Add surveys", + "Add ratings", + "Add feedback buttons", + "Observe user behavior patterns and infer needs rather than relying on explicit feedback" + ], + "answer": 3}, + + {"question": "A school wants to teach ethics more effectively. Which approach is most non-obvious but powerful?", + "choices": [ + "Teach moral philosophy", + "Discuss case studies", + "Invite guest speakers", + "Let students experience responsibility through real consequences in small community roles" + ], + "answer": 3}, + + {"question": "A social network wants users to feel more connected. Which proposal reflects deeper synthesis?", + "choices": [ + "Add more friend suggestions", + "Improve messaging", + "Add reactions", + "Design features that encourage shared vulnerability rather than surface interaction" + ], + "answer": 3}, + + {"question": "A company wants to reduce meetings without losing coordination. Which solution is the most creatively synthesized?", + "choices": [ + "Cancel half the meetings", + "Make meetings shorter", + "Use more async tools", + "Redesign decision ownership so coordination is structural rather than conversational" + ], + "answer": 3}, + + {"question": "A university wants students to choose better careers. Which approach reflects deeper synthesis?", + "choices": [ + "Provide more career talks", + "Add aptitude tests", + "Offer internships", + "Expose students to iterative exploration so preferences evolve through experience" + ], + "answer": 3}, + + {"question": "A city wants to encourage cycling. Which idea shows the most creative synthesis?", + "choices": [ + "Build bike lanes", + "Offer bike subsidies", + "Run awareness campaigns", + "Design neighborhoods where daily needs are naturally reachable by bike" + ], + "answer": 3}, + + {"question": "A platform wants creators to produce higher quality content. Which solution shows deeper synthesis?", + "choices": [ + "Pay more for views", + "Add quality guidelines", + "Feature top creators", + "Change algorithms to reward long-term audience retention over short-term engagement" + ], + "answer": 3}, + + {"question": "A company wants stronger organizational culture. Which proposal is least obvious but most synthesized?", + "choices": [ + "Write company values", + "Run team-building events", + "Create culture workshops", + "Align incentives and daily practices so culture emerges from behavior, not messaging" + ], + "answer": 3}, + + {"question": "A school wants students to become better critical thinkers. Which idea reflects deeper synthesis?", + "choices": [ + "Teach logic", + "Assign more essays", + "Debate topics", + "Have students critique and redesign existing systems rather than just analyze arguments" + ], + "answer": 3}, + + {"question": "A government wants better public trust. Which approach is the most creatively synthesized?", + "choices": [ + "Publish transparency reports", + "Hold press conferences", + "Use clearer language", + "Create participatory mechanisms where citizens experience real influence over outcomes" + ], + "answer": 3}, + + {"question": "A product struggles with feature bloat. Which response reflects deeper creative synthesis?", + "choices": [ + "Remove old features", + "Simplify the UI", + "Survey users", + "Redefine the core problem so the product shifts purpose rather than iterating on clutter" + ], + "answer": 3}, + + {"question": "A nonprofit wants volunteers to stay engaged long-term. Which idea shows non-obvious synthesis?", + "choices": [ + "Send appreciation emails", + "Offer certificates", + "Host social events", + "Let volunteers see the longitudinal impact of their specific contributions over time" + ], + "answer": 3}, + {"question": "A city wants to reduce youth vandalism. Which proposal reflects deeper synthesis?", + "choices": ["Increase fines", "Add more cameras", "Hire more guards", "Give young people shared ownership over public spaces they help design"], + "answer": 3}, + + {"question": "A company wants faster decision-making without chaos. Which idea shows creative synthesis?", + "choices": ["Remove approvals", "Add more managers", "Use more dashboards", "Clarify decision ownership so speed comes from structure, not urgency"], + "answer": 3}, + + {"question": "A school wants parents to be more involved. Which idea shows non-obvious synthesis?", + "choices": ["Send more emails", "Host more meetings", "Publish more grades", "Design activities where parents contribute skills rather than just receive information"], + "answer": 3}, + + {"question": "A platform wants users to provide more honest feedback. Which approach reflects deeper thinking?", + "choices": ["Add longer surveys", "Offer rewards", "Send reminders", "Create moments where feedback visibly changes outcomes so honesty feels worthwhile"], + "answer": 3}, + + {"question": "A hospital wants doctors to adopt a new protocol. Which proposal is most creatively synthesized?", + "choices": ["Mandate compliance", "Send training materials", "Track usage metrics", "Involve doctors in adapting the protocol so they feel authorship rather than obligation"], + "answer": 3}, + + {"question": "A startup wants to avoid building the wrong product. Which idea reflects deeper synthesis?", + "choices": ["Do more surveys", "Build faster MVPs", "Analyze competitors", "Spend time embedded in users’ real workflows before defining the product"], + "answer": 3}, + + {"question": "A city wants citizens to care more about local elections. Which approach is most non-obvious?", + "choices": ["Post more campaign ads", "Send reminders to vote", "Run debates", "Design civic processes where people see tangible effects of their participation between elections"], + "answer": 3}, + + {"question": "A company wants better cross-team collaboration. Which proposal reflects deeper synthesis?", + "choices": ["Add shared Slack channels", "Schedule more syncs", "Use collaboration tools", "Create shared goals that require interdependence rather than optional cooperation"], + "answer": 3}, + + {"question": "A school wants students to take more intellectual risks. Which approach is most creatively synthesized?", + "choices": ["Offer bonus points", "Praise participation", "Reduce workload", "Normalize public revision and iteration so mistakes are treated as visible progress"], + "answer": 3}, + + {"question": "A news organization wants to reduce misinformation spread. Which solution shows deeper synthesis?", + "choices": ["Add more fact checks", "Add warning labels", "Ban more users", "Change sharing mechanics so users pause and contextualize before amplifying content"], + "answer": 3}, + + {"question": "A company wants remote workers to feel more connected. Which proposal shows the most creative synthesis?", + "choices": ["More video calls", "Virtual happy hours", "Better cameras", "Create shared long-term projects where identity forms around contribution, not presence"], + "answer": 3}, + + {"question": "A school wants to discourage bullying. Which approach reflects deeper thinking?", + "choices": ["Stricter punishment", "More supervision", "Anti-bullying posters", "Shift peer status systems so kindness becomes socially rewarded rather than punished"], + "answer": 3}, + + {"question": "A product team wants users to explore more features. Which idea is least obvious but most effective?", + "choices": ["Add tutorials", "Add tooltips", "Send notifications", "Design workflows where advanced features become necessary to accomplish meaningful goals"], + "answer": 3}, + + {"question": "A city wants people to use public transport more. Which proposal reflects deeper synthesis?", + "choices": ["Lower ticket prices", "Run ad campaigns", "Add more buses", "Shape urban density so daily life naturally aligns with transit routes"], + "answer": 3}, + + {"question": "A nonprofit wants donors to give more consistently. Which idea shows non-obvious synthesis?", + "choices": ["Send more appeals", "Share emotional stories", "Offer tax reminders", "Let donors track the evolving impact of specific projects they helped fund"], + "answer": 3}, + + {"question": "A company wants more ethical behavior internally. Which approach reflects deeper synthesis?", + "choices": ["Write a code of conduct", "Run ethics training", "Add compliance checks", "Align incentives so unethical shortcuts are structurally unattractive"], + "answer": 3}, + + {"question": "A school wants students to become better collaborators. Which idea shows creative synthesis?", + "choices": ["More group work", "Teach teamwork theory", "Assign rotating leaders", "Design projects where success depends on genuine interdependence of roles"], + "answer": 3}, + + {"question": "A platform wants to reduce addiction-like usage. Which solution reflects deeper synthesis?", + "choices": ["Add usage limits", "Show screen-time stats", "Send warnings", "Redesign reward loops so value comes from completion rather than endless engagement"], + "answer": 3}, + + {"question": "A government wants better long-term infrastructure planning. Which proposal is most non-obvious?", + "choices": ["Hire more consultants", "Run more studies", "Increase funding", "Create institutional memory systems so lessons persist beyond political cycles"], + "answer": 3}, + + {"question": "A company wants more honest performance reviews. Which idea reflects deeper synthesis?", + "choices": ["Use anonymous forms", "Train managers", "Add calibration meetings", "Create continuous feedback norms so reviews are no longer rare high-stakes events"], + "answer": 3}, + + {"question": "A school wants students to read more deeply. Which proposal shows creative synthesis?", + "choices": ["Assign more pages", "Add comprehension quizzes", "Offer reading rewards", "Have students curate reading paths for others, making interpretation part of the task"], + "answer": 3}, + + {"question": "A city wants to reduce car usage downtown. Which approach reflects deeper synthesis?", + "choices": ["Increase parking fees", "Add bike ads", "Restrict traffic zones", "Redesign public spaces so walking becomes more pleasurable than driving"], + "answer": 3}, + + {"question": "A startup wants better user research. Which idea shows non-obvious synthesis?", + "choices": ["Run more interviews", "Collect more analytics", "Send more surveys", "Hire team members to temporarily live the user’s life instead of just studying it"], + "answer": 3}, + + {"question": "A company wants people to speak up about problems earlier. Which solution reflects deeper thinking?", + "choices": ["Add anonymous channels", "Encourage openness", "Run workshops", "Create visible examples where early dissent leads to praise rather than punishment"], + "answer": 3}, + + {"question": "A university wants stronger alumni relationships. Which idea shows creative synthesis?", + "choices": ["Send newsletters", "Host reunions", "Ask for donations", "Invite alumni into ongoing mentorship ecosystems rather than one-off events"], + "answer": 3}, + + {"question": "A product team wants to avoid overengineering. Which proposal reflects deeper synthesis?", + "choices": ["Set stricter deadlines", "Reduce scope", "Use fewer tools", "Continuously test assumptions with users so complexity is constrained by real need"], + "answer": 3}, + + {"question": "A company wants better succession planning. Which idea shows non-obvious synthesis?", + "choices": ["Identify high performers", "Offer leadership training", "Create talent pipelines", "Let multiple people shadow real decision-making long before promotion occurs"], + "answer": 3}, + + {"question": "A community wants people to care more for shared spaces. Which solution reflects deeper synthesis?", + "choices": ["Add more signage", "Increase cleaning staff", "Issue fines", "Create rituals and events that build emotional attachment to the space"], + "answer": 3}, + + {"question": "A company wants to improve long-term strategic thinking. Which idea is most creatively synthesized?", + "choices": ["Add quarterly planning", "Use forecasting tools", "Study competitors", "Encourage scenario-building exercises that explore multiple plausible futures"], + "answer": 3}, + + {"question": "A school wants to foster intrinsic motivation. Which approach reflects deeper synthesis?", + "choices": ["Give more rewards", "Praise more often", "Reduce difficulty", "Give students meaningful autonomy over projects rather than controlling outcomes"], + "answer": 3}, + + {"question": "A platform wants to prevent echo chambers. Which proposal reflects deeper thinking?", + "choices": ["Add diverse content", "Recommend opposing views", "Hide some posts", "Design interaction formats where disagreement happens within shared cooperative goals"], + "answer": 3}, + + {"question": "A company wants to reduce silos. Which solution shows creative synthesis?", + "choices": ["Restructure teams", "Add cross-team meetings", "Use shared tools", "Rotate ownership of real cross-cutting problems rather than roles"], + "answer": 3}, + + {"question": "A city wants citizens to recycle more. Which idea reflects non-obvious synthesis?", + "choices": ["Add more bins", "Increase fines", "Run awareness campaigns", "Make recycling socially visible so participation signals community belonging"], + "answer": 3}, + + {"question": "A product struggles with unclear value proposition. Which approach reflects deeper synthesis?", + "choices": ["Rewrite marketing copy", "Add more features", "Improve onboarding", "Clarify the core user transformation rather than listing functional benefits"], + "answer": 3}, + + {"question": "A company wants junior employees to grow faster. Which idea shows creative synthesis?", + "choices": ["Offer more courses", "Assign mentors", "Create learning plans", "Give ownership of small but real outcomes rather than simulated practice"], + "answer": 3}, + + {"question": "A school wants students to understand uncertainty better. Which approach reflects deeper thinking?", + "choices": ["Teach probability formulas", "Give more examples", "Use simulations", "Let students make predictions, track outcomes, and revise beliefs over time"], + "answer": 3}, + + {"question": "A government wants policies to survive leadership changes. Which proposal reflects deeper synthesis?", + "choices": ["Write stronger laws", "Build more agencies", "Increase oversight", "Embed policy goals into everyday institutions so continuity emerges culturally, not politically"], + "answer": 3}, + + {"question": "A company wants to reduce fear of failure. Which solution is most creatively synthesized?", + "choices": ["Say failure is okay", "Reward experimentation", "Share failure stories", "Publicly analyze failed experiments as valuable organizational knowledge"], + "answer": 3}, + + {"question": "A research lab wants more interdisciplinary breakthroughs. Which idea reflects deeper synthesis?", + "choices": ["Hire diverse experts", "Host more meetings", "Create shared documents", "Design shared problems that require multiple disciplines to make progress"], + "answer": 3}, +] \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..891e2d2 --- /dev/null +++ b/config.json @@ -0,0 +1,31 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 128000, + "torch_dtype": "float16", + "eos_token_id": 128009, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 14336, + "max_position_embeddings": 8192, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 32, + "num_hidden_layers": 32, + "num_key_value_heads": 8, + "pad_token_id": 128255, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_scaling": null, + "rope_theta": 500000.0, + "tie_word_embeddings": false, + "transformers_version": "4.57.6", + "unsloth_version": "2026.1.4", + "use_cache": true, + "vocab_size": 128256 +} \ No newline at end of file diff --git a/contextual reasoning eval questions and answers b/contextual reasoning eval questions and answers new file mode 100644 index 0000000..b164a26 --- /dev/null +++ b/contextual reasoning eval questions and answers @@ -0,0 +1,79 @@ +questions = [ + {"question": "A company improves efficiency by automating support, but customer trust declines. What perspective best explains this?", "choices": ["Automation is always negative", "Efficiency matters more than perception", "Technical gains can harm relational factors", "Customers dislike all change"], "answer": 2}, + {"question": "Why might a technically optimal solution fail in practice?", "choices": ["Because logic is flawed", "Because people resist math", "Because social and cultural context affects adoption", "Because optimization is impossible"], "answer": 2}, + {"question": "Which approach best reflects holistic decision-making?", "choices": ["Maximize one metric", "Ignore emotions", "Consider technical, social, and ethical impacts together", "Focus only on speed"], "answer": 2}, + {"question": "A public health campaign provides correct data but fails to change behavior. Why?", "choices": ["Data is useless", "People dislike authority", "Behavior depends on beliefs, trust, and culture", "The data must be wrong"], "answer": 2}, + {"question": "Which policy shows awareness of multiple stakeholders?", "choices": ["Maximize shareholder profit only", "Prioritize speed above all", "Balance employee wellbeing, profit, and community impact", "Ignore externalities"], "answer": 2}, + + {"question": "Why might improving school test scores not improve real education quality?", "choices": ["Students are lazy", "Teachers dislike metrics", "Teaching may narrow to the test instead of deeper learning", "Learning is random"], "answer": 2}, + {"question": "Which leader demonstrates holistic thinking?", "choices": ["One who focuses only on KPIs", "One who optimizes short-term gains", "One who considers morale, culture, outcomes, and incentives", "One who avoids complexity"], "answer": 2}, + {"question": "A city adds green spaces and later crime drops. What holistic explanation is plausible?", "choices": ["Plants reduce crime directly", "Crime decreased randomly", "Environmental design influences stress, community, and behavior", "Police vanished"], "answer": 2}, + {"question": "Why is focusing only on quarterly profits risky?", "choices": ["Profits are fake", "Markets are irrational", "It can undermine long-term sustainability and trust", "Accounting systems fail"], "answer": 2}, + {"question": "What does holistic medicine emphasize (non-mystically)?", "choices": ["Magic cures", "Ignoring science", "Considering lifestyle, stress, environment, and biology together", "Rejecting diagnosis"], "answer": 2}, + + {"question": "A policy reduces emissions but increases unemployment. What does holistic reasoning require?", "choices": ["Ignore unemployment", "Cancel the policy", "Consider tradeoffs and seek integrative solutions", "Assume one side is evil"], "answer": 2}, + {"question": "Why might two teams with identical tools perform differently?", "choices": ["Random luck", "Tools don't matter", "Team dynamics, communication, and culture influence outcomes", "One team cheats"], "answer": 2}, + {"question": "Why is user experience design inherently holistic?", "choices": ["It is subjective", "It ignores logic", "It integrates psychology, usability, context, and emotion", "It avoids structure"], "answer": 2}, + {"question": "What best explains why urban planning requires holistic reasoning?", "choices": ["Cities are unpredictable", "Data is unavailable", "Transportation, housing, economics, and social factors interact", "Politics interferes"], "answer": 2}, + {"question": "Why might a health intervention succeed in one country but fail in another?", "choices": ["Health is random", "Doctors are worse elsewhere", "Cultural, economic, and trust contexts differ", "People resist medicine"], "answer": 2}, + + {"question": "Which is a holistic critique of algorithmic hiring systems?", "choices": ["Algorithms are evil", "Math is flawed", "They may reinforce bias through social and historical data", "Computers are slow"], "answer": 2}, + {"question": "A school bans phones and grades improve but anxiety increases. What does holistic analysis suggest?", "choices": ["Phones are irrelevant", "Grades matter more than wellbeing", "Both academic and emotional impacts should be evaluated", "Students are fragile"], "answer": 2}, + {"question": "Why is purely technical optimization often insufficient in public policy?", "choices": ["Politicians are corrupt", "Data is scarce", "Human behavior and incentives shape real outcomes", "Math fails in society"], "answer": 2}, + {"question": "Which framing best reflects global thinking?", "choices": ["Solve only local issues", "Ignore external impacts", "Consider how actions affect interconnected systems worldwide", "Avoid complexity"], "answer": 2}, + {"question": "Why might economic growth harm wellbeing?", "choices": ["Growth is bad", "People dislike money", "Environmental damage and inequality can offset material gains", "Statistics lie"], "answer": 2}, + + {"question": "Which product decision reflects holistic design?", "choices": ["Maximize clicks", "Minimize cost only", "Balance usability, ethics, sustainability, and business goals", "Copy competitors"], "answer": 2}, + {"question": "Why might strict workplace monitoring reduce productivity?", "choices": ["Monitoring never works", "Workers become lazy", "Loss of autonomy harms motivation and trust", "Technology fails"], "answer": 2}, + {"question": "A company relocates offices to cut costs but loses talent. Why?", "choices": ["Talent is irrational", "Cities are expensive", "Work-life balance, community, and lifestyle influence retention", "Recruiting failed"], "answer": 2}, + {"question": "Why do effective climate solutions require interdisciplinary thinking?", "choices": ["Science is insufficient", "Politics blocks progress", "Technology, economics, behavior, and governance must align", "Nature is unpredictable"], "answer": 2}, + {"question": "What is a holistic approach to mental health?", "choices": ["Ignore biology", "Only prescribe medication", "Consider therapy, environment, relationships, sleep, and purpose", "Assume personality is fixed"], "answer": 2}, + + {"question": "Why can improving road safety increase traffic volume?", "choices": ["Drivers become careless", "Cars multiply spontaneously", "People feel safer and drive more often", "Statistics are misleading"], "answer": 2}, + {"question": "Why do successful organizations invest in culture, not just strategy?", "choices": ["Culture is fashionable", "Strategy is irrelevant", "Shared values shape behavior across the whole system", "Employees demand it"], "answer": 2}, + {"question": "Which is an example of contextual reasoning?", "choices": ["Applying the same rule everywhere", "Ignoring circumstances", "Adjusting decisions based on environment and constraints", "Rejecting consistency"], "answer": 2}, + {"question": "Why might standardized solutions fail in education?", "choices": ["Teachers are stubborn", "Students differ widely in needs and context", "Curriculum is flawed", "Schools resist change"], "answer": 1}, + {"question": "What makes sustainability a holistic concept?", "choices": ["It is political", "It is vague", "It balances environmental, economic, and social dimensions", "It rejects growth"], "answer": 2}, + + {"question": "Why might charity donations fail to solve poverty?", "choices": ["Charity is bad", "People misuse money", "Structural factors like education, policy, and opportunity matter", "Aid is always corrupt"], "answer": 2}, + {"question": "Why is healthcare policy inherently complex?", "choices": ["Doctors disagree", "Technology changes fast", "Costs, ethics, access, culture, and outcomes interact", "Patients are irrational"], "answer": 2}, + {"question": "Which reasoning best reflects integrative thinking?", "choices": ["Either/or framing", "Single-cause explanation", "Both/and synthesis across perspectives", "Random selection"], "answer": 2}, + {"question": "Why might fast growth harm startup health?", "choices": ["Growth is bad", "Founders get tired", "Culture, systems, and communication may not scale properly", "Investors interfere"], "answer": 2}, + {"question": "Why might purely data-driven decisions still fail?", "choices": ["Data is useless", "Humans are emotional", "Data may omit important qualitative context", "Models are too complex"], "answer": 2}, + + {"question": "Which policy shows holistic urban planning?", "choices": ["Add parking everywhere", "Widen roads only", "Integrate housing, transport, green space, and accessibility", "Focus only on downtown"], "answer": 2}, + {"question": "Why does food policy involve more than agriculture?", "choices": ["Because food is cultural", "Because farms are inefficient", "Health, economics, environment, and equity are intertwined", "Because trade interferes"], "answer": 2}, + {"question": "What does holistic risk assessment consider?", "choices": ["Only probability", "Only financial cost", "Technical, human, reputational, and systemic impacts", "Only worst-case scenarios"], "answer": 2}, + {"question": "Why might increasing police presence alone not reduce crime long-term?", "choices": ["Police are ineffective", "Crime is genetic", "Education, poverty, trust, and opportunity influence outcomes", "Statistics are flawed"], "answer": 2}, + {"question": "Why is burnout often a systemic issue, not just individual weakness?", "choices": ["People lack resilience", "Work is naturally exhausting", "Workload, expectations, culture, and support shape mental health", "People dislike effort"], "answer": 2}, + + {"question": "Which design choice shows holistic product thinking?", "choices": ["Maximize engagement only", "Add features endlessly", "Consider accessibility, ethics, usability, and impact together", "Follow trends"], "answer": 2}, + {"question": "Why do cultural misunderstandings harm international projects?", "choices": ["Languages differ", "People are irrational", "Norms, expectations, and communication styles shape outcomes", "Education systems fail"], "answer": 2}, + {"question": "Why might a technically correct message still fail to persuade?", "choices": ["Truth is irrelevant", "Logic never works", "Trust, framing, emotion, and identity influence reception", "Audiences are ignorant"], "answer": 2}, + {"question": "Why does biodiversity contribute to ecosystem stability?", "choices": ["It looks attractive", "It slows evolution", "Different species provide complementary resilience functions", "It prevents all extinction"], "answer": 2}, + {"question": "Why is parenting advice rarely universal?", "choices": ["Parents resist change", "Children behave randomly", "Each child develops within a unique context and environment", "Psychology is flawed"], "answer": 2}, + + {"question": "Which is a holistic critique of fast fashion?", "choices": ["Clothes are ugly", "Trends change quickly", "Environmental, labor, and cultural impacts are interconnected", "Consumers are careless"], "answer": 2}, + {"question": "Why is accessibility a holistic design concern?", "choices": ["It benefits only a minority", "It increases cost", "Design choices affect usability across diverse users and contexts", "It slows development"], "answer": 2}, + {"question": "Why do effective interventions often require community involvement?", "choices": ["Communities demand control", "It looks inclusive", "Local knowledge and trust shape real-world success", "Experts are unnecessary"], "answer": 2}, + {"question": "Why can economic inequality affect public health outcomes?", "choices": ["Poor people are unhealthy", "Doctors are biased", "Stress, access, environment, and opportunity interact systemically", "Statistics exaggerate"], "answer": 2}, + {"question": "Why might technology amplify rather than solve social problems?", "choices": ["Technology is evil", "Users misuse tools", "Tools interact with incentives, power, and existing structures", "Innovation is overrated"], "answer": 2}, + + {"question": "Why is climate change described as a 'wicked problem'?", "choices": ["It is political", "It is unsolvable", "It involves intertwined scientific, economic, cultural, and ethical dimensions", "It lacks data"], "answer": 2}, + {"question": "Why might strict rules reduce ethical behavior?", "choices": ["Rules are ineffective", "People dislike authority", "People may focus on compliance instead of responsibility", "Ethics are subjective"], "answer": 2}, + {"question": "Which scenario reflects holistic leadership?", "choices": ["Cut staff to improve metrics", "Ignore employee emotions", "Balance performance, wellbeing, long-term vision, and values", "Follow competitors blindly"], "answer": 2}, + {"question": "Why might global supply chains be fragile?", "choices": ["Shipping is slow", "Companies are greedy", "Economic, political, environmental, and logistical dependencies interact", "Markets fluctuate"], "answer": 2}, + {"question": "Why is public trust essential in vaccination programs?", "choices": ["People are emotional", "Science is weak", "Social perception affects participation and outcomes", "Media interferes"], "answer": 2}, + + {"question": "Which framing reflects holistic ethics?", "choices": ["Follow rules blindly", "Maximize profit", "Consider consequences, intentions, relationships, and context", "Avoid moral complexity"], "answer": 2}, + {"question": "Why might removing art programs harm overall education?", "choices": ["Art is essential", "Teachers prefer creativity", "Creative skills support emotional, cognitive, and social development", "Students get bored"], "answer": 2}, + {"question": "Why does migration policy require holistic analysis?", "choices": ["Borders are political", "Data is unreliable", "Economic, humanitarian, cultural, and legal factors intersect", "Governments disagree"], "answer": 2}, + {"question": "Why can 'best practices' fail when copied across organizations?", "choices": ["Organizations are unique", "Managers resist change", "Context determines effectiveness, not just technique", "Training is insufficient"], "answer": 2}, + {"question": "Why might economic aid destabilize local economies?", "choices": ["Aid is bad", "Governments misuse funds", "External money can disrupt incentives and local markets", "People become dependent"], "answer": 2}, + + {"question": "Which question best reflects holistic inquiry?", "choices": ["What is the fastest fix?", "Who is to blame?", "How do the interacting factors shape the overall outcome?", "Which metric improved?"], "answer": 2}, + {"question": "Why is interdisciplinarity important in complex research?", "choices": ["It is fashionable", "Single fields are outdated", "Different lenses reveal different aspects of the same reality", "Experts prefer collaboration"], "answer": 2}, + {"question": "Why do ecosystems collapse when one species is removed?", "choices": ["Nature is fragile", "Species are random", "Interdependence among species shapes system balance", "Climate always changes"], "answer": 2}, + {"question": "Why might improving technology not improve quality of life?", "choices": ["Technology is overrated", "People misuse devices", "Social structures and values shape how technology affects wellbeing", "Progress is illusion"], "answer": 2}, + {"question": "Which is the clearest sign of holistic thinking?", "choices": ["Certainty and simplicity", "Single-variable explanations", "Comfort with complexity and multiple 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Over time, congestion returns to previous levels or worsens. What best explains this outcome?", + "choices": [ + "Drivers become less skilled over time", + "More roads always create more accidents", + "Increased road capacity encourages more people to drive, offsetting gains", + "Public transport becomes less efficient" + ], + "answer": 2 + }, + { + "id": 2, + "category": "Systemic Scenarios", + "question": "A company rewards employees solely based on number of tickets closed per day. After several months, customer satisfaction drops. What is the most plausible explanation?", + "choices": [ + "Employees forgot how to solve complex problems", + "Employees optimized for speed rather than quality", + "Customers became more demanding", + "The software system slowed down" + ], + "answer": 1 + }, + { + "id": 3, + "category": "Systemic Scenarios", + "question": "In an ecosystem, wolves are removed. Initially, deer population grows rapidly, but after some years the deer population collapses. What systemic dynamic best explains this?", + "choices": [ + "Deer naturally die after population booms", + "Wolves controlled disease directly", + "Overgrazing reduced food availability, leading to starvation", + "Climate change occurred suddenly" + ], + "answer": 2 + }, + { + "id": 4, + "category": "Systemic Scenarios", + "question": "A government caps rent prices to make housing more affordable. Which long-term effect is most consistent with systems-level reasoning?", + "choices": [ + "Landlords universally become more generous", + "More luxury housing gets built", + "Housing supply may shrink as incentives to build decline", + "All tenants become long-term renters" + ], + "answer": 2 + }, + { + "id": 5, + "category": "Systemic Scenarios", + "question": "A social media platform optimizes for time spent on site. Over time, political polarization increases. Why is this a systems effect rather than a simple bug?", + "choices": [ + "Users misunderstand the interface", + "Algorithms were programmed incorrectly", + "Feedback loops amplify emotionally engaging content", + "Servers introduce random noise" + ], + "answer": 2 + }, + { + "id": 6, + "category": "Systemic Scenarios", + "question": "A hospital reduces staffing to cut costs. Short-term savings occur, but long-term costs rise. What best explains this?", + "choices": [ + "Hospitals are naturally inefficient", + "Reduced staff increases burnout and errors, causing higher downstream costs", + "Patients become more careless", + "Insurance companies change policies" + ], + "answer": 1 + }, + { + "id": 7, + "category": "Feedback Loops", + "question": "Which scenario best illustrates a reinforcing feedback loop?", + "choices": [ + "Thermostat maintaining room temperature", + "Predator-prey population oscillation", + "Viral content attracting attention, which increases visibility, attracting more attention", + "Random coin flips" + ], + "answer": 2 + }, + { + "id": 8, + "category": "Systemic Scenarios", + "question": "A country subsidizes fuel to help the poor. Over time, traffic worsens and pollution increases. What systemic tradeoff is occurring?", + "choices": [ + "Subsidies always fail", + "Lower prices increase consumption, creating negative externalities", + "Citizens dislike public transportation", + "Fuel companies manipulate supply" + ], + "answer": 1 + }, + { + "id": 9, + "category": "Complexity", + "question": "Why are delayed consequences particularly dangerous in complex systems?", + "choices": [ + "They are always unpredictable", + "They prevent immediate feedback, making harmful policies seem successful at first", + "They only occur in natural systems", + "They can be ignored safely" + ], + "answer": 1 + }, + { + "id": 10, + "category": "Holistic Thinking", + "question": "A company automates customer service to reduce costs. Which outcome reflects holistic reasoning?", + "choices": [ + "Costs decrease, therefore the decision is good", + "Automation is always better than humans", + "Customer frustration may rise, affecting brand trust and long-term revenue", + "AI systems never fail" + ], + "answer": 2 + }, + { + "id": 11, + "category": "Complexity", + "question": "Which policy is most likely to produce unintended consequences due to system complexity?", + "choices": [ + "Updating a typo on a website", + "Changing a font style in a document", + "Basing school funding solely on standardized test scores", + "Replacing broken light bulbs" + ], + "answer": 2 + }, + { + "id": 12, + "category": "System Control", + "question": "Why do complex systems often resist simple top-down control?", + "choices": [ + "Because rules are never effective", + "Because participants are irrational", + "Because agents adapt their behavior in response to interventions", + "Because leaders lack intelligence" + ], + "answer": 2 + }, + { + "id": 13, + "category": "Second-Order Effects", + "question": "Which example best shows second-order effects?", + "choices": [ + "It rains, the ground gets wet", + "A student studies and gets a good grade", + "More police reduce crime immediately", + "More police reduce crime, which raises property values, which displaces low-income residents" + ], + "answer": 3 + }, + { + "id": 14, + "category": "Optimization", + "question": "Why might optimizing a single metric harm overall system performance?", + "choices": [ + "Metrics are inherently flawed", + "People dislike being measured", + "Optimization can distort behavior away from broader system goals", + "Systems prefer randomness" + ], + "answer": 2 + }, + { + "id": 15, + "category": "Leverage Points", + "question": "Which intervention best reflects leverage-point thinking?", + "choices": [ + "Punishing every individual mistake", + "Changing incentives that shape behavior across the system", + "Adding more rules to cover every edge case", + "Ignoring the problem" + ], + "answer": 1 + }, + { + "id": 16, + "category": "Sustainability", + "question": "A fishing community increases fishing capacity to boost income. Years later, fish stocks collapse. What was the missing systems insight?", + "choices": [ + "Fish reproduce randomly", + "Fishing boats were poorly designed", + "Resource extraction exceeded regenerative capacity", + "Markets fluctuate unpredictably" + ], + "answer": 2 + }, + { + "id": 17, + "category": "Resilience", + "question": "Why is diversity often important in resilient systems?", + "choices": [ + "It makes systems harder to understand", + "It ensures redundancy and adaptability to change", + "It slows performance", + "It eliminates all failures" + ], + "answer": 1 + }, + { + "id": 18, + "category": "Path Dependence", + "question": "Which situation best demonstrates path dependence?", + "choices": [ + "A coin flip outcome", + "Choosing randomly each time", + "Early technology adoption shaping long-term market dominance", + "A perfectly balanced system returning to equilibrium" + ], + "answer": 2 + }, + { + "id": 19, + "category": "Holistic Thinking", + "question": "Which framing best reflects holistic thinking?", + "choices": [ + "Focus only on the fastest measurable outcome", + "Treat each department as fully independent", + "Consider technical, social, emotional, and economic factors together", + "Assume all problems have single causes" + ], + "answer": 2 + }, + { + "id": 20, + "category": "Systemic Failure", + "question": "Why do well-intentioned interventions sometimes worsen the problem they aim to solve?", + "choices": [ + "Because people are irrational", + "Because complex systems contain hidden feedback loops and incentives", + "Because planning is always bad", + "Because effort is pointless" + ], + "answer": 1 + }, + { + "id": 21, + "category": "Resilience", + "question": "A system is 'resilient' but not 'robust'. What is the difference?", + "choices": [ + "Resilience is strength, Robustness is speed", + "Robustness resists change; Resilience absorbs change and recovers", + "Robustness is for machines; Resilience is for humans", + "There is no difference" + ], + "answer": 1 + }, + { + "id": 22, + "category": "Archetypes", + "question": "What is the 'tragedy of the commons'?", + "choices": [ + "A theatre play about poverty", + "When individual rational incentives lead to the depletion of a shared resource", + "When governments take over private property", + "A failure of individual morality" + ], + "answer": 1 + }, + { + "id": 23, + "category": "Complexity", + "question": "Which describes an 'emergent property'?", + "choices": [ + "The sum of the parts is equal to the whole", + "Properties that appear in a system but are not present in the individual parts", + "A property that disappears when a system grows", + "A predictable byproduct of linear growth" + ], + "answer": 1 + }, + { + "id": 24, + "category": "System Dynamics", + "question": "In systems thinking, what is a 'stock'?", + "choices": [ + "A share in a company", + "The foundation of a building", + "An accumulation of something (water, money, trust) over time", + "A flow that changes quickly" + ], + "answer": 2 + }, + { + "id": 25, + "category": "Feedback Loops", + "question": "A 'balancing feedback loop' is primarily intended to:", + "choices": [ + "Increase growth exponentially", + "Maintain stability or reach a goal", + "Cause the system to collapse", + "Increase the speed of the system" + ], + "answer": 1 + }, + { + "id": 26, + "category": "Optimization", + "question": "Why does 'local optimization' often lead to 'global sub-optimization'?", + "choices": [ + "Local managers are less intelligent", + "Improving one part in isolation can disrupt the balance of the whole system", + "Global goals are usually impossible to meet", + "Competition is always bad" + ], + "answer": 1 + }, + { + "id": 27, + "category": "Complexity", + "question": "What happens in a 'tipping point'?", + "choices": [ + "The system returns to its original state", + "A small change triggers a massive, often irreversible shift in system state", + "The system becomes perfectly balanced", + "Progress slows down significantly" + ], + "answer": 1 + }, + { + "id": 28, + "category": "Cognitive Bias", + "question": "Which is an example of 'Sunk Cost Fallacy' affecting a system?", + "choices": [ + "Investing more in a failing project just because a lot has already been spent", + "Saving money for a future project", + "Calculating the ROI of a new venture", + "Selling an asset at a profit" + ], + "answer": 0 + }, + { + "id": 29, + "category": "Rationality", + "question": "What is 'bounded rationality'?", + "choices": [ + "People are completely irrational", + "People make rational decisions based on the limited information and time they have", + "Rationality is only possible in mathematics", + "Systems are more rational than individuals" + ], + "answer": 1 + }, + { + "id": 30, + "category": "Risk", + "question": "How does 'tight coupling' affect system risk?", + "choices": [ + "It makes systems more efficient and safer", + "It allows failures in one part to spread rapidly to others", + "It isolates problems effectively", + "It has no effect on risk" + ], + "answer": 1 + }, + { + "id": 31, + "category": "Incentives", + "question": "The 'Cobra Effect' describes what?", + "choices": [ + "A snake's movement", + "When an incentive for a problem results in people creating more of the problem to get the reward", + "The fear of sudden changes", + "A successful biological intervention" + ], + "answer": 1 + }, + { + "id": 32, + "category": "Complexity", + "question": "In a 'complex adaptive system', agents:", + "choices": [ + "Follow a central commander", + "Change their strategies based on experience and the environment", + "Never interact with each other", + "Act randomly at all times" + ], + "answer": 1 + }, + { + "id": 33, + "category": "Archetypes", + "question": "What is 'shifting the burden'?", + "choices": [ + "Giving a task to a colleague", + "Using a short-term fix that undermines the long-term health of the system", + "Improving the efficiency of a workflow", + "Moving a physical load" + ], + "answer": 1 + }, + { + "id": 34, + "category": "Measurement", + "question": "Which is a 'lagging indicator' of a system's health?", + "choices": [ + "The current rate of investment", + "The profit from last year", + "The mood of the employees today", + "The number of new leads" + ], + "answer": 1 + }, + { + "id": 35, + "category": "Entropy", + "question": "What is 'entropy' in a system?", + "choices": [ + "The increase in energy", + "The natural tendency toward disorder and loss of information", + "A method for organizing files", + "The speed of light" + ], + "answer": 1 + }, + { + "id": 36, + "category": "Feedback Loops", + "question": "A 'virtuous cycle' is another name for:", + "choices": [ + "A balancing loop", + "A reinforcing loop with positive outcomes", + "A cycle that never changes", + "A moral philosophy" + ], + "answer": 1 + }, + { + "id": 37, + "category": "Stability", + "question": "What is 'homeostasis'?", + "choices": [ + "Moving to a new home", + "A system maintaining its internal environment within narrow limits", + "The study of humans", + "A type of rapid growth" + ], + "answer": 1 + }, + { + "id": 38, + "category": "Complexity", + "question": "What describes 'Equifinality'?", + "choices": [ + "All systems end the same way", + "Reaching the same end state from different starting points and in different ways", + "A final decision that cannot be changed", + "The death of a system" + ], + "answer": 1 + }, + { + "id": 39, + "category": "Lindy Effect", + "question": "The 'Lindy Effect' suggests that for non-perishable things (like ideas):", + "choices": [ + "They die young", + "Their future life expectancy is proportional to their current age", + "Newer is always better", + "The end is always near" + ], + "answer": 1 + }, + { + "id": 40, + "category": "Ergodicity", + "question": "What is 'Ergodicity'?", + "choices": [ + "A type of energy", + "When the average of a group represents the likely experience of an individual over time", + "The study of work efficiency", + "A logical fallacy" + ], + "answer": 1 + }, + { + "id": 41, + "category": "Goodhart's Law", + "question": "What is 'Goodhart’s Law'?", + "choices": [ + "Laws should be followed", + "When a measure becomes a target, it ceases to be a good measure", + "Everything that can go wrong will", + "The simplest explanation is best" + ], + "answer": 1 + }, + { + "id": 42, + "category": "Supply Chain", + "question": "In 'The Beer Game' (supply chain simulation), the 'Bullwhip Effect' is caused by:", + "choices": [ + "Aggressive managers", + "Lack of communication and time delays in information flowing up the chain", + "A shortage of raw materials", + "High prices" + ], + "answer": 1 + }, + { + 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