Methodology — the formula, the twenty-cell weight table, and the Boeing recovery.
A living document. The formula is settled. The weight table is v0 and the response coefficient ρ has a v0 protocol; both are in methodological review toward v1. The open points are listed honestly in §7.
An index that is a product, not a sum.
Fab City Index 3.0 is defined for a pilot — a city read against its bioregional context — at time $t$ as the product of three terms drawn from the twenty-cell Full-Stack Metrics matrix:
The product matters. High DIDO with high PITO is performative — fab labs without metabolic shift. Low PITO with low DIDO is a depleted city, not a Fab City — neither extracting much nor generating much. Only the combination — capacity plus metabolic shift plus coupling to action — counts. The $(1-\mathrm{PITO}_t)$ term reframes PITO from an absolute load into a distance walked off the linear-extractive baseline.
The trajectory form — the version that actually answers the central question of the 2054 pledge — is $\Delta\mathrm{FCI}/\Delta t$, the rate at which a city is fab-cityifying. With at least quarterly resolution over a 36-month horizon, the trajectory is what the PLANETAI substrate is built to measure.
Two metabolic signatures.
PITO — Products In, Trash Out — is the metabolic signature of a city operating in the linear-extractive mode. PITO measures what the city receives and rejects: imports of products, energy, food and raw materials; exports of waste, emissions and externalised pollution. Expressed as a stock variable in $[0,1]$; high PITO means heavy linear-extractive metabolism.
DIDO — Data In, Data Out — is the metabolic signature of a city operating in the regenerative-distributed mode. DIDO measures what the city generates and circulates: open data infrastructure, fab-lab activity, distributed manufacturing capacity, recycling and remanufacturing capacity, community sensing, institutional transparency, and the policy / research / innovation layer that allows the city to act on what it knows. High DIDO means the city has built — and uses — the cognitive and productive capacity to substitute imported product with local design and local making.
The terms were coined by Vicente Guallart and Neil Gershenfeld in the early Barcelona Fab City period, and are documented in the 2014 and 2016 Fab City white papers (Diez). We are not inventing them. We are operationalising them.
Why both axes, why not collapse to one. A city can have very high DIDO and still very high PITO (Barcelona is closer to this than people would like). A city can have low DIDO and low PITO for bad reasons — sparse instrumentation hiding both flows. The two-axis frame keeps the diagnostic crisp. A single-number index hides this; the original 37/100 is a single number and its weakness is exactly that you cannot tell what is happening underneath.
How the four-pillar by five-scale matrix maps onto PITO and DIDO.
Each cell $c$ in the matrix carries a PITO weight $w_c^{\mathrm{PITO}}$ and a DIDO weight $w_c^{\mathrm{DIDO}}$, both in $[0,1]$, summing to 1. The weights are not philosophical — they are documented assignments derived from what the cell actually measures. Cells that measure throughput weight toward PITO; cells that measure capacity, transparency, or institutional response weight toward DIDO. The Generation 1+2 cell — Economic × City / Region — is highlighted. Aggregation stops at the Region tier: the Bioregion and Planet rows enter PITO and DIDO as boundary-condition observations — context for the city reading — never as scales the index rolls up to.
| Pillar × Scale | Primary measurement | PITO weight | DIDO weight | Notes |
|---|
Three v0 cells flagged for sharpened argument before the canonical weights harden: Economic × Bioregion (0.8 / 0.2), Environmental × Community (0.5 / 0.5), Economic × Community (0.3 / 0.7).
From cell scores to the index.
Each cell $c$ produces a normalised score $s_c \in [0,1]$ using Boeing's discipline — priority × self-sufficiency where formal data exists; documented proxy where it does not, with mock-pill labelling. PITO and DIDO at time $t$ are weighted means of cell scores under their respective weight assignments:
$s_c^{\text{extractive}}$ is the cell's score interpreted as throughput; $s_c^{\text{capacity}}$ is the same cell's score interpreted as regenerative capacity. Both indices are bounded in $[0,1]$. Most cells contribute to one side meaningfully and the other faintly, in proportion to their weights; only Economic × City (0.5 / 0.5) and Environmental × Community (0.5 / 0.5) contribute to both axes equally.
The respect move.
This is the most important methodological point for readers of this prototype. Boeing's Hamburg score and Utopies' Paris score are both single-cell, single-snapshot computations at Economic × Region (or × City depending on data scope), with no DIDO term and $\rho$ implicit at 1.
Setting all weights to zero except Economic × Region, dropping the coupling term, and computing only the self-sufficiency dimension:
The derivation also exposes the structural reason both cities scored ~37: at Economic × Region with public data only and no dynamic component, the most diversified Western metros land at the same bound because the underlying material flows are governed by global supply-chain structure, not local policy. The way to move the number is by activating DIDO and ρ — exactly what FCI 3.0 measures.
From snapshot to metabolism.
$\rho_t \in [0,1]$ measures action latency — the speed at which an observation at any tier produces a fitted, human-approved response at the appropriate governance tier within a pre-registered budget. $\rho = 1$ means perfect coupling — every observation generates a fitted action within deadline. $\rho = 0$ means observations are made but never acted on.
Generations 1 and 2 have $\rho$ implicit at 1 because the model is not dynamic. Generation 3 makes $\rho$ measurable and treats it as the third axis. Without ρ the index is a snapshot. With ρ the index is a metabolism — which is what the 2054 Pledge has always implicitly asked us to measure.
$\rho$ is also where the falsifiable hypothesis $\mathrm{H}_0\text{-A}$ binds. Per-scale observation-action cycle logging — Community, City and Region, with individual opt-in observations entering through Community-tier aggregation (open item C1) — is wired into the prototype skeleton and fills in as live ingestion lands, even at low data volume.
Tier-weighting and council-rejection handling are deferred in the v0 protocol notes — open items in the v0 methodology, in review toward a v1 protocol.
What is not yet defended.
- Twelve of twenty cells are meaningfully populated in current FCI 3.0 methodology work. The Region tier and the Governance × Bioregion / × Region cells are the thinnest. Either populated honestly with mock-pill discipline or named as deferred research deliverables.
- The 4×5 → PITO/DIDO weight table is v0. Three cells deserve sharpened argument before the canonical weights harden — Economic × Bioregion, Environmental × Community, Economic × Community. All three are in methodological review toward v1.
- The Boeing numerical recovery example is sketched, not formal. A worked Hamburg numerical example using public NACE / COICOP data closes the loop and pre-empts the most predictable reviewer objection. An open item in the v0 methodology.
- The ρ measurement protocol is drafted as a v0 note; tier-weighting and council-rejection handling are open.
- Vivanco's matrix is a working paper plus a 2025 doctoral thesis, not yet peer-reviewed in its own right; a bioregional peer-matching companion paper would fix that.
- LOCAL SHIFT® and LOCAL FOOTPRINT® Nature are proprietary Utopies products. We cite the published methodology and the 2018 numbers; we do not claim reproducibility of the simulator outputs.
Naming these in the body of the methodology is the price of the credibility we are asking readers for.