Use Case · Methodology
Auditing anchor tenants on the transmutation quadrant.
A methodology any community can run on a hyperscale tenant, a real-estate developer, a utility, or any institution whose footprint dominates a neighbourhood. Per-Maslow F and A scoring with stated assumptions, the six-input audit protocol, and the policy levers the scoring informs. Worked example: the Economy of Wisdom Foundation's evaluation of the Telus Sovereign AI Factory Vancouver.
The accounting gap
When a large institution lands inside an urban core, the public evaluation runs on two scoreboards. One records throughput: capital, jobs, square footage, projected economic activity. The other records nothing because no instrument exists for it: deprivation absorbed and fulfillment emitted across the population the facility now sits inside.
The framework treats an anchor tenant as a single high-magnitude node in a relational network. F is the deprivation the node filters (absorbs and does not pass downstream). A is the fulfillment the node emits in excess of what it received. The node's profile against its host city is the unit of audit.
Step 1: name the denominator
Score the host city, neighbourhood, or service area on its current unmet need across all five Maslow levels. Use publicly available baselines:
- Physiological. Homelessness count, food-bank visit volume, rental vacancy, household energy burden.
- Safety. Crime rates, police-call response times, eviction filings, ER readmission rates.
- Belonging. Community-centre throughput, third-place density, loneliness survey indices, neighbourhood-association membership.
- Esteem. Employment density, sectoral signalling, scholarship and award volume.
- Actualization. Research output, civic-tech activity, public-goods production capacity.
Without an explicit denominator the audit reduces to anecdote. A tenant that creates 50 jobs in a city with 2,000 unhoused residents is different from a tenant that creates 50 jobs in a city with 50.
Step 2: score F and A per Maslow level
For each level, score F (filtering of deprivation) and A (amplification of fulfillment) on a −10 to +10 scale, with the source for each value attached. Compute Mₙ = τF + A per level, then the weighted sum across levels using w = {5, 4, 3, 2, 1}.
- Positive F at a level means the tenant absorbs deprivation at that level without passing it downstream. A waste-heat recovery system that reduces tenant utility bills is positive physiological F. A child-care subsidy for staff that reduces parental stress is positive safety F.
- Negative F at a level means the tenant amplifies deprivation at that level. A construction-period traffic plan that increases pedestrian-collision risk in a school zone is negative safety F.
- Positive A at a level means the tenant emits more fulfillment than it receives. Open public access to a building atrium creates belonging-level A. Sectoral signalling that draws related employers to the city creates esteem-level A.
- Negative A at a level means the tenant absorbs fulfillment without re-emission. A site that occupies a parcel previously planned for housing absorbs the physiological-level A that housing would have produced.
State every assumption. State which flows are excluded from the score (typically: flows to the tenant's shareholders, flows to general tax bases, flows to populations outside the audited service area). The audit is reproducible only if the assumptions are visible.
Step 3: compute placement and sensitivity
The per-level weighted sum gives W, the tenant's net moral work to the host. The aggregate F and A divided by total weight, scaled to the −100 / +100 axis, give the tenant's coordinates on the live quadrant.
Run sensitivity at τ = 0.8 (flourishing focus), τ = 1.0 (default), and τ = 1.5 (cycle-breaking focus). If the quadrant placement does not flip across that range, the verdict is robust. If it flips, the verdict depends on which civic value is in play, and the audit needs to surface that.
Three intervention archetypes the audit informs
Condition the public funding on physiological-level outcomes.
Public capital flowing to an anchor tenant (federal grants, provincial guarantees, municipal tax abatements, utility rate concessions) is the strongest lever the audit identifies. Tie a measurable fraction of the public contribution to verified delivery of housing units, food infrastructure, or energy-cost reduction in the host city. Without this conditioning, the framework predicts the public subsidy accrues to the tenant's shareholders; the denominator captures no measurable benefit.
Make the utility service agreement measure delivered M, not delivered MW.
Industrial utility rate classes typically optimize for predictable demand. A τ-weighted load tariff for large industrial customers in supply-constrained service territory prices the displacement cost: the next units of marginal capacity that would otherwise have served residential growth or building electrification. The framework's per-Maslow weighting gives the utility an explicit hierarchy when allocating constrained capacity.
Use the Community Benefit Agreement to convert provisional M into delivered M.
CBAs are the standard instrument for translating tenant promises into binding obligations. A CBA that is explicitly Maslow-tagged (each line item identified by which need level it addresses) is auditable against the framework. CBAs whose substance is not on the public record cannot be scored, and the framework's central estimate treats them as zero until they are.
The six-input audit protocol
An audited placement (as distinct from a provisional one based on public-record reasoning) requires six inputs from the tenant or from regulators:
- Audited multi-year capital, opex, and revenue allocation by site.
- Utility service agreement: rate class, demand pattern, peak draw, contracted vs interruptible portions, any private power-purchase agreements that offset utility allocation.
- Any community-benefit infrastructure delivered (e.g. recovered heat in GWh per year, on-site community space in sq ft, scholarships or community grants in dollars), measured at the point of delivery.
- Long-term FTE count by site and by role, with a breakdown of net-new vs relocated positions.
- Community Benefit Agreement terms and dollar value, with each line item tagged to a Maslow level.
- Public funding amount and instrument, with any community-benefit conditions documented.
With those six inputs, the per-level F and A scores become point estimates with sourced derivations. Without them, the placement is provisional and explicitly so.
Worked example
The Economy of Wisdom Foundation has run this methodology on the Telus Sovereign AI Factory Vancouver, announced May 11, 2026. Two downtown Vancouver sites, 150 megawatts of BC Hydro capacity targeted by 2032, federal Sovereign AI funding under negotiation. The audit applies the steps above against a denominator that includes 2,715 unhoused residents (2025 City of Vancouver count) and 832,000 annual food-bank visits (2025 Greater Vancouver Food Bank).
The full evaluation, with sources and the published quadrant placement, is at economyofwisdom.org/blog/2026-05-23-telus-datacenter-vancouver/. The provisional dot is plotted on the live quadrant explorer for reference.
What the framework does not do
It does not judge any individual at the audited institution. A Magnifier or Extractor classification describes a system state of high amplification with low filtering. The classification reports flows through the institution. The named author of any cited corporate, government, or media document is acting inside institutional incentive structures; the framework's purpose is to make those incentive structures visible.
It also does not predict outcomes. A provisional placement is the best estimate today. The placement moves as the audited inputs land. Publishing the framework and the math lets that move be verified in either direction by anyone with the source data.