Extreme heat
→ school disruption
→ weaker learning
→ health stress
→ higher energy demand
→ family cost pressure
→ weaker child inheritance floor

Civilisation is operational,
but several base floors are strained at the same time.
The main danger is not one dramatic global collapse.
The main danger is slow normalisation of shrinking corridors,
weaker repair capacity, and burnt rooms.

If one shock affects children + schools + health + food/water at the same time,
move warning to Orange or Red.

Stop bleeding.
Protect children, schools, clinics, food, water, and trusted communication first.

If emergency measures become normal operating mode,
move warning to Orange.
If normal services can no longer recover between shocks,
move warning to Red.

Convert emergency response into permanent resilience upgrades.
Build climate-safe schools, local food buffers, water resilience,
energy access, learning repair, and local repair crews.

If a base floor is still officially present but no longer performs reliably,
move warning to Red.
If the official map says a corridor exists but ordinary people cannot use it,
classify as collapsed-in-function.

Protect repair capacity.
Use base-floor budgeting, PlanetOS accounting, child-first investment,
trusted evidence systems, and long-term infrastructure repair.

If today’s children are likely to inherit fewer safe rooms,
fewer usable corridors, and higher repair debt,
raise the 25-year warning level.

Widen the future floor.
Protect childhood, regenerate PlanetOS, strengthen education transfer,
make technology public-good infrastructure, and build local repair capacity.

1-YEAR:
Watch for shocks.
5-YEAR:
Watch for repeated shocks becoming normal.
10-YEAR:
Watch for normal systems redesigning downward.
25-YEAR:
Watch what children inherit.

What happened?

What is beginning to weaken?
Which corridor may collapse next?
Which burnt room is forming before people notice?
What will children inherit in 1, 5, 10, and 25 years if the signal is ignored?

children
food
water
health
education
energy
climate
biodiversity
safety
displacement
trust
information
finance
technology
infrastructure
local repair capacity

STATUS:
  Civilisation is operational.
WARNING:
  Several base floors are decaying at the same time.
RISK:
  Corridor collapse becomes normalised.
CORE QUESTION:
  Are we repairing future floor space faster than we are burning it?

DOMAIN WARNING:
  “Flood risk is rising.”
CivEWS WARNING:
  Flood risk is rising
  → school disruption risk rises
  → food supply risk rises
  → displacement risk rises
  → public finance pressure rises
  → child future-floor loss risk rises.

2026 = current floor
2027 = next floor
2031 = 5-year floor
2036 = 10-year floor
2051 = 25-year inheritance floor

DECAY:
  rooms still exist, but quality weakens.
COLLAPSE:
  corridors still exist, but people can no longer pass safely.
BURNT ROOM:
  the option is gone for the people who needed it.

SIGNAL INTAKE
→ Scout Layer
→ Source Quality Filter
→ PlanetOS Warehouse
→ Crosswalk Engine
→ Sensor Fusion
→ Time-Horizon Engine
→ Corridor Collapse Calculator
→ Burnt-Room Risk Calculator
→ Repair Priority Engine
→ Purple Report Warning Output

Climate Scout
Food Scout
Water Scout
Health Scout
Education Scout
Child Scout
Energy Scout
Displacement Scout
Conflict Scout
Finance Scout
Trust / Information Scout
Technology Scout
Infrastructure Scout
PlanetOS Scout
Local Repair Scout

WAREHOUSE ROOMS:
  CHILDREN
  FOOD
  WATER
  HEALTH
  EDUCATION
  ENERGY
  PLANETOS
  SAFETY
  TRUST
  FINANCE
  TECHNOLOGY
  LOCAL_REPAIR

primary institutions
official datasets
peer-reviewed research
UN / World Bank / WHO / WMO / IEA / UNESCO / UNICEF / UNHCR / FAO / UNDRR sources
national statistical agencies
reputable scientific bodies
transparent methodology reports

1-YEAR WARNING:
  immediate decay and shock risk.
5-YEAR WARNING:
  near-term corridor collapse risk.
10-YEAR WARNING:
  structural floor narrowing risk.
25-YEAR WARNING:
  child inheritance and civilisation trajectory risk.

food price shock
school closure risk
extreme heat season
disease outbreak
aid funding gap
election trust crisis
energy supply disruption
flood/drought/cyclone risk
displacement surge

repeated climate disruption to schools
chronic food insecurity
rising debt service crowding out public repair
repeated public-health system overload
normalisation of humanitarian aid dependency
insurance retreat from high-risk zones
teacher shortage becoming structural

coastal adaptation failure
lost learning cohort
declining water reliability
degraded soil and crop zones
structural unemployment after automation
public trust degradation
infrastructure maintenance debt

smaller future floor
lost climate-safe settlements
lost biodiversity buffers
intergenerational learning loss
institutional trust collapse
technology inequality hardening into class structure
permanent migration corridors
civilisation repair deficit

GREEN:
  Floor stable. Watch normally.
YELLOW:
  Early decay signal. Monitor and repair early.
ORANGE:
  Corridor narrowing. Act before collapse.
RED:
  Corridor collapsing. Stabilise immediately.
BLACK:
  Burnt-room condition. Function lost or nearly lost.

GREEN  = P3 / P2
YELLOW = P1 early decay
ORANGE = P1 severe decay / P0.7 early collapse
RED    = P0.7 collapse / P0.3 partial collapse
BLACK  = P0.0 burnt room

WATCHES:
  child poverty
  nutrition
  school attendance
  displacement
  child labour
  mental health
  violence exposure
  access to identity, healthcare, and learning
EARLY WARNING:
  children begin absorbing adult system failure.

WATCHES:
  hunger
  food insecurity
  staple prices
  crop shocks
  fertilizer cost
  supply-chain disruption
  food import dependency
  school meal coverage
EARLY WARNING:
  households shift from healthy diets to survival diets.

WATCHES:
  drought
  groundwater
  unsafe water
  sanitation gaps
  river stress
  flood contamination
  water conflict
  irrigation reliability
EARLY WARNING:
  water reliability becomes a daily-life constraint.

WATCHES:
  outbreak risk
  vaccine coverage
  health workforce
  clinic overload
  medicine shortages
  heat-health mortality
  maternal and child health
  mental-health pressure
EARLY WARNING:
  public health shifts from prevention to emergency response.

WATCHES:
  attendance
  learning outcomes
  teacher capacity
  school closures
  digital divide
  climate disruption
  conflict disruption
  transfer failure
EARLY WARNING:
  schooling remains present but learning transfer weakens.

WATCHES:
  electricity access
  grid reliability
  clean cooking
  fuel prices
  diesel dependency
  renewable deployment
  school and clinic power
  energy affordability
EARLY WARNING:
  energy inequality blocks education, health, connectivity, and enterprise.

WATCHES:
  heat
  rainfall
  drought
  floods
  storms
  sea level
  biodiversity loss
  soil degradation
  ocean heat
  wildfire risk
  ecosystem buffers
EARLY WARNING:
  Earth-system stress begins damaging human corridors directly.

WATCHES:
  conflict
  violence
  displacement
  refugees
  internally displaced people
  humanitarian access
  aid funding gaps
  documents and legal identity
  host-community pressure
EARLY WARNING:
  normal life routes are replaced by survival routes.

WATCHES:
  misinformation
  institutional trust
  election trust
  public health trust
  crisis communication
  AI-generated distortion
  media fragmentation
  evidence quality
EARLY WARNING:
  societies cannot coordinate around a shared repair map.

WATCHES:
  debt service
  fiscal space
  aid flows
  climate finance
  insurance retreat
  infrastructure backlog
  household debt
  repair budget cuts
EARLY WARNING:
  repair is delayed because the maintenance fuel is missing.

WATCHES:
  AI access
  cyber risk
  digital public infrastructure
  digital divide
  child online safety
  open learning tools
  health AI
  automation labour risk
EARLY WARNING:
  technology widens elite floors faster than base floors.

WATCHES:
  local technicians
  maintenance capacity
  procurement quality
  community trust
  school and clinic repair
  water-system maintenance
  local data quality
  local emergency response
EARLY WARNING:
  tools exist, but communities cannot operate or maintain them.

What could break, spike, or collapse within the next annual floor?

food price shock
heatwave season
flood/drought/cyclone risk
school disruption
disease outbreak
displacement surge
energy price shock
trust crisis
aid funding gap

1_YEAR_WARNING:
  immediate deterioration risk
  acute shock risk
  emergency corridor risk

IF:
  heat risk rises
  + school cooling is weak
  + children already show learning gaps
THEN:
  Education Floor enters ORANGE warning.
REPAIR:
  heat-safe school protocols
  school cooling
  backup learning continuity
  attendance monitoring

1. Activate emergency dashboards.
2. Protect schools and clinics first.
3. Monitor food, water, heat, disease, and displacement weekly.
4. Use trusted local communication.
5. Deploy rapid repair funds.
6. Keep children inside safe corridors.

Which repeated stresses are becoming structural corridors of failure?

repeated climate disruptions
persistent hunger
learning loss cohorts
teacher shortage
health workforce shortage
debt service pressure
migration pressure
insurance withdrawal
AI/digital inequality
public trust erosion

5_YEAR_WARNING:
  recurring shock becomes structural weakness
  emergency response becomes normal operating mode

IF:
  schools close repeatedly due to floods or heat
  + learning gaps widen
  + repair funding is delayed
THEN:
  Education Corridor moves from Decaying to Collapsing.
REPAIR:
  climate-safe school design
  hybrid learning continuity
  catch-up learning
  teacher support
  local repair budget

1. Convert emergency responses into permanent resilience upgrades.
2. Build climate-safe schools and clinics.
3. Fund water, food, and energy resilience.
4. Create youth repair corps and local technician pipelines.
5. Strengthen digital public infrastructure with rights protection.
6. Build trusted public evidence systems.

Which base floors are being redesigned downward?

coastal retreat
chronic water stress
soil degradation
lost learning cohorts
AI labour displacement
public finance squeeze
institutional trust loss
biodiversity buffer loss
infrastructure maintenance debt
child poverty persistence

10_YEAR_WARNING:
  base floor narrows structurally
  the next generation has fewer normal routes

IF:
  public finance weakens
  + adaptation cost rises
  + education and health are underfunded
THEN:
  Repair Capacity Floor enters RED warning.
REPAIR:
  debt-to-resilience swaps
  child-first budgeting
  base-floor budgeting
  transparent repair ledgers

1. Protect national repair capacity.
2. Treat PlanetOS as infrastructure.
3. Shift from growth-only planning to floor-space planning.
4. Prevent permanent learning and health deficits.
5. Build climate migration and settlement planning.
6. Strengthen institutional trust and evidence systems.

What will children inherit when they become adult operators?

child poverty
learning transfer
climate-safe settlement
ecosystem buffers
food and water reliability
institutional trust
debt inheritance
technology access
civilisation repair capability
future opportunity width

25_YEAR_WARNING:
  inheritance-floor forecast
  future-room availability
  burnt-room accumulation
  civilisation capability trajectory

IF:
  child poverty remains high
  + education transfer weakens
  + climate damage rises
  + trust declines
THEN:
  2051 Future Floor narrows.
REPAIR:
  child-first investment
  PlanetOS regeneration
  learning repair
  universal energy and connectivity
  trust infrastructure
  local repair civilisation

1. Make children the primary inheritance sensor.
2. Measure whether the future floor is widening or narrowing.
3. Protect Earth-system buffers.
4. Prevent technology inequality from hardening.
5. Build education for civilisation literacy.
6. Track burnt rooms across generations.

SIGNAL:
  extreme heat increases.
PLANETOS:
  heat risk rises.
HEALTHOS:
  heat illness and mortality risk rise.
EDUCATIONOS:
  school disruption and learning fatigue rise.
ENERGYOS:
  cooling demand rises.
FINANCEOS:
  household and public energy costs rise.
GOVERNANCEOS:
  emergency response pressure rises.
FAMILYOS:
  household stress rises.
CHILDOS:
  child learning and health risk rise.
CivEWS OUTPUT:
  heat is not only weather.
  heat is a multi-floor corridor warning.

SIGNAL:
  food prices rise.
FOODOS:
  affordability weakens.
FAMILYOS:
  household trade-offs increase.
CHILDOS:
  nutrition risk rises.
EDUCATIONOS:
  learning energy falls.
HEALTHOS:
  disease vulnerability rises.
GOVERNANCEOS:
  social stability pressure rises.
FINANCEOS:
  subsidy / aid pressure rises.
CivEWS OUTPUT:
  food price stress may become child-floor and trust-floor stress.

0   = no warning
25  = weak signal
50  = moderate warning
75  = strong warning
100 = severe warning

SEVERITY:
  how bad the signal is.
SPEED:
  how fast it is worsening.
SCALE:
  how many people / systems it affects.
DEPENDENT_FLOORS:
  how many other floors depend on it.
CHILD_IMPACT:
  how strongly it affects children.
IRREVERSIBILITY:
  how hard it is to undo.
REPAIR_GAP:
  how weak the repair response is.
SOURCE_CONFIDENCE:
  how strong the evidence is.

EARLY_WARNING_SCORE =
  severity * 0.18
+ speed * 0.14
+ scale * 0.14
+ dependent_floors * 0.14
+ child_impact * 0.16
+ irreversibility * 0.12
+ repair_gap * 0.12

ADJUSTED_WARNING =
  early_warning_score * source_confidence

100 = 1.00
80  = 0.80
60  = 0.60

0–24:
  GREEN
25–49:
  YELLOW
50–69:
  ORANGE
70–84:
  RED
85–100:
  BLACK

def classify_warning(score):
    if score >= 85:
        return "BLACK_BURNT_ROOM_WARNING"
    if score >= 70:
        return "RED_CORRIDOR_COLLAPSE_WARNING"
    if score >= 50:
        return "ORANGE_CORRIDOR_NARROWING_WARNING"
    if score >= 25:
        return "YELLOW_DECAY_WARNING"
    return "GREEN_STABLE_WATCH"

def clamp(value, low=0, high=100):
    return max(low, min(high, value))
def calculate_early_warning_score(
    severity,
    speed,
    scale,
    dependent_floors,
    child_impact,
    irreversibility,
    repair_gap,
    source_confidence
):
    raw_score = (
        severity * 0.18
        + speed * 0.14
        + scale * 0.14
        + dependent_floors * 0.14
        + child_impact * 0.16
        + irreversibility * 0.12
        + repair_gap * 0.12
    )
    adjusted_score = raw_score * (source_confidence / 100)
    return clamp(round(adjusted_score, 1))
def classify_warning(score):
    if score >= 85:
        return {
            "level": "BLACK",
            "state": "BURNT_ROOM_WARNING",
            "meaning": "Function is lost or close to lost for affected populations."
        }
    if score >= 70:
        return {
            "level": "RED",
            "state": "CORRIDOR_COLLAPSE_WARNING",
            "meaning": "Corridor is failing under load and needs immediate stabilisation."
        }
    if score >= 50:
        return {
            "level": "ORANGE",
            "state": "CORRIDOR_NARROWING_WARNING",
            "meaning": "Corridor is narrowing and needs targeted repair."
        }
    if score >= 25:
        return {
            "level": "YELLOW",
            "state": "DECAY_WARNING",
            "meaning": "Early decay signal. Monitor and repair early."
        }
    return {
        "level": "GREEN",
        "state": "STABLE_WATCH",
        "meaning": "No major warning, but continue monitoring."
    }

More weight on speed and acute severity.

HORIZON_WEIGHTS_1Y = {
    "severity": 0.22,
    "speed": 0.22,
    "scale": 0.12,
    "dependent_floors": 0.10,
    "child_impact": 0.14,
    "irreversibility": 0.08,
    "repair_gap": 0.12
}

More weight on repeated stress and repair gap.

HORIZON_WEIGHTS_5Y = {
    "severity": 0.17,
    "speed": 0.15,
    "scale": 0.14,
    "dependent_floors": 0.15,
    "child_impact": 0.16,
    "irreversibility": 0.10,
    "repair_gap": 0.13
}

More weight on dependent floors and irreversibility.

HORIZON_WEIGHTS_10Y = {
    "severity": 0.14,
    "speed": 0.12,
    "scale": 0.14,
    "dependent_floors": 0.18,
    "child_impact": 0.16,
    "irreversibility": 0.14,
    "repair_gap": 0.12
}

More weight on child impact, inheritance value, and irreversibility.

HORIZON_WEIGHTS_25Y = {
    "severity": 0.12,
    "speed": 0.08,
    "scale": 0.13,
    "dependent_floors": 0.17,
    "child_impact": 0.22,
    "irreversibility": 0.18,
    "repair_gap": 0.10
}

def calculate_horizon_warning(signal, weights):
    raw_score = (
        signal["severity"] * weights["severity"]
        + signal["speed"] * weights["speed"]
        + signal["scale"] * weights["scale"]
        + signal["dependent_floors"] * weights["dependent_floors"]
        + signal["child_impact"] * weights["child_impact"]
        + signal["irreversibility"] * weights["irreversibility"]
        + signal["repair_gap"] * weights["repair_gap"]
    )
    adjusted_score = raw_score * (signal["source_confidence"] / 100)
    return clamp(round(adjusted_score, 1))

signal = {
    "signal_id": "PLANETOS.HEAT.2026.001",
    "name": "Extreme Heat and School Disruption",
    "source_type": "WMO_UNICEF_UNDRR",
    "source_confidence": 90,
    "affected_floors": [
        "PLANETOS",
        "HEALTH",
        "EDUCATION",
        "ENERGY",
        "CHILDREN",
        "FINANCE",
        "LOCAL_REPAIR"
    ],
    "severity": 75,
    "speed": 70,
    "scale": 80,
    "dependent_floors": 90,
    "child_impact": 85,
    "irreversibility": 65,
    "repair_gap": 70
}

def process_signal_all_horizons(signal):
    scores = {}
    horizon_sets = {
        "1_year": HORIZON_WEIGHTS_1Y,
        "5_year": HORIZON_WEIGHTS_5Y,
        "10_year": HORIZON_WEIGHTS_10Y,
        "25_year": HORIZON_WEIGHTS_25Y
    }
    for horizon, weights in horizon_sets.items():
        score = calculate_horizon_warning(signal, weights)
        scores[horizon] = {
            "score": score,
            "warning": classify_warning(score)
        }
    return {
        "signal_id": signal["signal_id"],
        "name": signal["name"],
        "affected_floors": signal["affected_floors"],
        "horizon_scores": scores
    }

signals = [
    {
        "signal_id": "PLANETOS.CLIMATE.HEAT.001",
        "name": "Extreme Heat Stress",
        "source_type": "WMO_UNDRR_HEALTH",
        "source_confidence": 90,
        "affected_floors": [
            "PLANETOS", "HEALTH", "EDUCATION", "ENERGY",
            "CHILDREN", "FINANCE", "LOCAL_REPAIR"
        ],
        "severity": 78,
        "speed": 75,
        "scale": 85,
        "dependent_floors": 90,
        "child_impact": 82,
        "irreversibility": 65,
        "repair_gap": 70
    },
    {
        "signal_id": "FOOD.INSECURITY.001",
        "name": "Food Insecurity and Nutrition Stress",
        "source_type": "FAO_UNICEF_WFP_WORLD_BANK",
        "source_confidence": 88,
        "affected_floors": [
            "FOOD", "CHILDREN", "HEALTH", "EDUCATION",
            "FINANCE", "TRUST", "SAFETY"
        ],
        "severity": 75,
        "speed": 60,
        "scale": 82,
        "dependent_floors": 88,
        "child_impact": 90,
        "irreversibility": 70,
        "repair_gap": 68
    },
    {
        "signal_id": "EDUCATION.CLIMATE.DISRUPTION.001",
        "name": "Climate-Driven School Disruption",
        "source_type": "UNICEF_UNESCO_WMO",
        "source_confidence": 88,
        "affected_floors": [
            "EDUCATION", "CHILDREN", "PLANETOS", "FAMILY",
            "TECHNOLOGY", "LOCAL_REPAIR"
        ],
        "severity": 70,
        "speed": 68,
        "scale": 78,
        "dependent_floors": 82,
        "child_impact": 95,
        "irreversibility": 72,
        "repair_gap": 70
    },
    {
        "signal_id": "DISPLACEMENT.GLOBAL.001",
        "name": "Forced Displacement and Route Loss",
        "source_type": "UNHCR_IOM_UNOCHA",
        "source_confidence": 92,
        "affected_floors": [
            "SAFETY", "CHILDREN", "EDUCATION", "HEALTH",
            "FOOD", "TRUST", "FINANCE", "LOCAL_REPAIR"
        ],
        "severity": 85,
        "speed": 72,
        "scale": 82,
        "dependent_floors": 95,
        "child_impact": 95,
        "irreversibility": 78,
        "repair_gap": 76
    },
    {
        "signal_id": "TRUST.REALITY.FRAGMENTATION.001",
        "name": "Accepted Reality Fragmentation",
        "source_type": "MEDIA_TRUST_RESEARCH_PUBLIC_SIGNAL",
        "source_confidence": 70,
        "affected_floors": [
            "TRUST", "GOVERNANCE", "HEALTH", "CLIMATE",
            "EDUCATION", "SAFETY", "TECHNOLOGY"
        ],
        "severity": 70,
        "speed": 75,
        "scale": 80,
        "dependent_floors": 95,
        "child_impact": 75,
        "irreversibility": 70,
        "repair_gap": 75
    },
    {
        "signal_id": "FINANCE.REPAIR.GAP.001",
        "name": "Repair Finance and Debt Pressure",
        "source_type": "WORLD_BANK_IMF_UN_SDG",
        "source_confidence": 82,
        "affected_floors": [
            "FINANCE", "EDUCATION", "HEALTH", "WATER",
            "PLANETOS", "ENERGY", "LOCAL_REPAIR"
        ],
        "severity": 72,
        "speed": 60,
        "scale": 78,
        "dependent_floors": 95,
        "child_impact": 82,
        "irreversibility": 68,
        "repair_gap": 82
    },
    {
        "signal_id": "TECH.AI.INEQUALITY.001",
        "name": "AI and Digital Inequality",
        "source_type": "UNICEF_UNESCO_OECD_PUBLIC_DATA",
        "source_confidence": 75,
        "affected_floors": [
            "TECHNOLOGY", "EDUCATION", "FINANCE", "TRUST",
            "WORK", "CHILDREN", "GOVERNANCE"
        ],
        "severity": 65,
        "speed": 85,
        "scale": 78,
        "dependent_floors": 85,
        "child_impact": 85,
        "irreversibility": 72,
        "repair_gap": 70
    }
]

def process_all_signals(signals):
    results = []
    for signal in signals:
        result = process_signal_all_horizons(signal)
        results.append(result)
    return results
def rank_signals_by_horizon(results, horizon):
    return sorted(
        results,
        key=lambda x: x["horizon_scores"][horizon]["score"],
        reverse=True
    )

def generate_civews_control_tower(signals):
    results = process_all_signals(signals)
    return {
        "system_id": "EKSG.PR.CivEWS.PLANETOS.EARLYWARNING.v1.0",
        "system_name": "The Purple Report Civilisation Early Warning System",
        "horizons": {
            "1_year": rank_signals_by_horizon(results, "1_year"),
            "5_year": rank_signals_by_horizon(results, "5_year"),
            "10_year": rank_signals_by_horizon(results, "10_year"),
            "25_year": rank_signals_by_horizon(results, "25_year")
        },
        "all_results": results
    }

CivEWS CONTROL TOWER
1-YEAR WARNING:
  What may break soon?
5-YEAR WARNING:
  What repeated stress may become structural?
10-YEAR WARNING:
  What base floors may redesign downward?
25-YEAR WARNING:
  What will children inherit?
TOP SIGNALS:
  1. Displacement and route loss
  2. PlanetOS heat and climate disruption
  3. Education disruption
  4. Food insecurity
  5. Repair finance gap
  6. Trust and accepted reality fragmentation
  7. AI and digital inequality

TOP RISKS:
  extreme heat / flood / storm disruption
  food affordability stress
  displacement and humanitarian overload
  school disruption
  aid funding gaps
  trust and misinformation events

PRIORITY:
  protect children
  keep schools open safely
  protect clinics
  monitor food and water
  fund rapid repair
  maintain trusted communication

TOP RISKS:
  repeated school disruption becomes learning loss
  climate adaptation gap widens
  chronic food and water stress hardens
  displacement becomes semi-permanent
  public finance pressure weakens repair
  AI/digital inequality hardens

PRIORITY:
  climate-safe schools
  energy for clinics
  water resilience
  local food buffers
  digital public infrastructure
  learning repair systems

TOP RISKS:
  some regions face structural climate-floor narrowing
  education cohorts lose capability
  local ecosystems lose recovery capacity
  debt and insurance gaps reduce adaptation
  trust degradation weakens public repair
  automation shifts labour corridors

PRIORITY:
  PlanetOS accounting
  base-floor budgeting
  child-first investment
  nature-based infrastructure
  learning-to-work transition repair
  trusted evidence systems

TOP RISKS:
  children inherit a narrower floor
  climate-safe settlement space shrinks
  biodiversity and water buffers decline
  technology inequality becomes social architecture
  institutional trust loss becomes inherited culture
  repair capacity fails to match accumulated damage

PRIORITY:
  protect childhood
  regenerate PlanetOS
  strengthen education transfer
  build local repair capability
  make AI and technology public-good infrastructure
  prevent burnt-room normalisation

ACTION:
  monitor
  diagnose
  repair early
  prevent maintenance debt

ACTION:
  stabilise corridor
  fund local repair
  protect children
  activate cross-floor dashboard

ACTION:
  emergency intervention
  stop bleeding
  create alternate routes
  surge finance
  trusted public communication

ACTION:
  protect life
  rebuild minimum viable function
  restore records
  relocate if necessary
  long-term reconstruction

REGISTRY.ID:
  EKSG.PR.CivEWS.PLANETOS.EARLYWARNING.v1.0
PUBLIC.NAME:
  The Purple Report | Civilisation Early Warning System
SHORT.NAME:
  CivEWS
CORE.DEFINITION:
  CivEWS is a PlanetOS early-warning system that detects civilisation decay,
  corridor collapse, burnt-room risk, and future inheritance loss across
  1-year, 5-year, 10-year, and 25-year time horizons.
CORE.METAPHOR:
  Civilisation is a high-rise building through time.
  Each year is a new floor.
  Base floors carry upper floors.
  Corridors are usable life routes.
  Burnt rooms are lost future options.
TIME.HORIZONS:
  1_YEAR:
    immediate shock and acute decay.
  5_YEAR:
    repeated stress becoming structural weakness.
  10_YEAR:
    base-floor redesign downward.
  25_YEAR:
    child inheritance and civilisation trajectory.
WARNING.LEVELS:
  GREEN:
    stable watch.
  YELLOW:
    decay warning.
  ORANGE:
    corridor narrowing warning.
  RED:
    corridor collapse warning.
  BLACK:
    burnt-room warning.
SCOUTS:
  Climate_Scout
  Food_Scout
  Water_Scout
  Health_Scout
  Education_Scout
  Child_Scout
  Energy_Scout
  Displacement_Scout
  Conflict_Scout
  Finance_Scout
  Trust_Information_Scout
  Technology_Scout
  Infrastructure_Scout
  PlanetOS_Scout
  Local_Repair_Scout
WAREHOUSE.ROOMS:
  CHILDREN
  FOOD
  WATER
  HEALTH
  EDUCATION
  ENERGY
  PLANETOS
  SAFETY
  TRUST
  FINANCE
  TECHNOLOGY
  LOCAL_REPAIR
SIGNAL.VARIABLES:
  severity
  speed
  scale
  dependent_floors
  child_impact
  irreversibility
  repair_gap
  source_confidence
EARLY.WARNING.FORMULA:
  early_warning_score =
    severity * 0.18
  + speed * 0.14
  + scale * 0.14
  + dependent_floors * 0.14
  + child_impact * 0.16
  + irreversibility * 0.12
  + repair_gap * 0.12
ADJUSTMENT:
  adjusted_warning = early_warning_score * source_confidence
CROSSWALK.RULE:
  No signal is read in isolation.
  Every warning must be crosswalked across affected OS floors.
PLANETOS.LAW:
  A warning matters most when one floor’s weakness begins transmitting into
  other floors.
CHILD.INHERITANCE.LAW:
  25-year warnings are scored by what children will inherit as adult operators.
FINAL.VERDICT:
  CivEWS exists to detect burnt rooms before they become normal,
  collapsing corridors before they fail,
  and decaying base floors while repair is still cheap.

Civilisation is not failing everywhere,
but several base floors are under simultaneous strain.
The danger is not only sudden collapse.
The danger is slow normalisation of burnt rooms.
The repair task is to detect decay early,
stabilise corridors before collapse,
rebuild rooms where loss has already occurred,
and widen the future floor before children arrive.

Civilisation is operational,
but several base floors are under simultaneous pressure.
The biggest 2026 hazard is not only one disaster.
It is signal stacking:
climate shock + conflict + food insecurity + displacement + weak funding + trust breakdown.

El Niño / heat / rainfall shock
→ crop and water stress
→ food prices
→ child nutrition
→ school attendance
→ health burden
→ public finance pressure
→ trust pressure

food insecurity
→ cheaper/lower-quality diets
→ child malnutrition
→ weaker learning energy
→ health burden
→ family stress
→ social instability

conflict / route disruption
→ displacement
→ school loss
→ health access loss
→ aid cost increase
→ food insecurity
→ host-system overload
→ trust and governance pressure

outbreak + weak health system
→ clinic overload
→ school/work disruption
→ misinformation
→ trust loss
→ delayed response
→ higher mortality and repair cost

geoeconomic confrontation
→ shipping / fuel / insurance stress
→ food and aid cost rise
→ inflation
→ public finance pressure
→ household stress
→ trust and political pressure

misinformation / AI distortion
→ accepted reality fragments
→ public action weakens
→ repair instructions fail
→ crisis lasts longer
→ trust debt rises

funding gap
→ aid cut
→ food/health/shelter/school support weakens
→ local systems overloaded
→ displacement and hunger worsen
→ future repair cost rises

school disruption
→ learning loss
→ weaker confidence
→ weaker skills
→ weaker future income
→ weaker local repair capacity

energy/logistics stress
→ food and medical supply cost
→ clinic/school disruption
→ household inflation
→ aid-delivery failure
→ trust pressure

AI/digital divide
→ unequal learning and work access
→ trust stress
→ labour transition stress
→ class-floor hardening
→ 25-year inheritance split

1. Extreme heat alerts.
2. Flood, storm, drought, wildfire warnings.
3. Food-price spikes.
4. Humanitarian access disruptions.
5. Aid funding percentages.
6. Conflict escalation around chokepoints.
7. Outbreak alerts from WHO.
8. School closure and attendance reports.
9. Energy and fuel price spikes.
10. Misinformation surges during crises.

1. ENSO / El Niño updates.
2. Hunger hotspot updates.
3. Displacement and refugee data.
4. Humanitarian appeal funding.
5. Climate disaster losses.
6. Public debt and fiscal stress.
7. Vaccination and outbreak trends.
8. School disruption and learning recovery.
9. AI/cyber incidents affecting public systems.
10. Insurance retreat from climate-risk zones.

1. Whether emergency responses are becoming normal.
2. Whether aid cuts are creating invisible burnt rooms.
3. Whether repeated climate shocks are damaging schools and clinics.
4. Whether food insecurity is moving into famine-risk territory.
5. Whether trust erosion is blocking repair.
6. Whether technology is widening or narrowing education access.
7. Whether local repair capacity is improving or falling behind.

If one event affects 3 or more base floors,
raise warning by one level.

heatwave
→ health + schools + energy + food + water
= raise warning

If children’s nutrition, schooling, safety, or health are affected,
raise warning by one level.

If aid, public finance, or local maintenance cannot respond,
raise warning by one level.

If normal service is replaced by emergency routing,
classify as collapsing corridor.

If a service officially exists but people cannot use it,
classify as collapsed-in-function.

2026 STATUS:
  ORANGE overall.
RED ZONES:
  climate-exposed regions,
  conflict and displacement corridors,
  hunger hotspots,
  underfunded humanitarian systems,
  health-emergency settings.
MAIN HAZARD:
  stacked stress.
MAIN WATCH:
  climate + conflict + food + displacement + funding + trust.
MAIN CIVILISATION WARNING:
  The world may not collapse at the top.
  It may narrow from the bottom.
MAIN CHILD-INHERITANCE WARNING:
  Every missed school year, failed food corridor, displaced childhood,
  untreated illness, or climate-burnt settlement becomes a missing future room.
MAIN REPAIR RULE:
  Watch early, repair early, protect children first,
  and do not let burnt rooms become normal.