◆ PROTOTYPE / DEMO — scores are illustrative sample data to show the format. In production, values pull from public county/state datasets via the PHIT™ Datahub. ◆
← Command Center

My Girl Power PHIT™ Community Score Card

Pima County / Tucson · Women & Girls Advocacy
★ Built by the My Girl Power Squad
Coach Lucy
💡 Coach Lucy's Coaches Tip

Lead with your gaps, brag about your girls.

Your two lowest scores — Childcare (39) and Economic Equity (44) — sit below every peer group. That's your loudest case at Call to the Public: "We're below the state AND the nation on childcare." Then flip it: Girls' Leadership is 72 — beating Arizona and U.S. peers. That's My Girl Power working. The story writes itself: we're building the next generation of women leaders, but the childcare and pay gaps threaten to undo it. Bring this card to the Board of Supervisors.

The six issues — at a glance

Every issue has its own tab with the full breakdown. Click any card to open it.

What am I comparing against? Read this once — the four benchmarks aren't interchangeable

The trend — interactive

Pick a time range. Click any line in the legend to remove it. Hover a point for its value. The legend is ordered highest to lowest, so it matches what you see.

Coach Lucy
💡 Coach Lucy's Coaches Tip

Use this overlay to ask questions, never to score points. The most useful thing on this chart isn't which party was in office — it's that the line moves slowly under everyone. Childcare didn't collapse in one administration and it won't be fixed in one. That's actually the Commission's strongest argument: this is a structural problem that outlasts terms, which is exactly why a permanent, nonpartisan Commission exists. If a commissioner uses this chart to blame a party, she's handed the other side a reason to ignore us. Bring the gap. Ask for the fix. Stay out of the fight.

Compared to other counties

Same index, other places. Toggle between Arizona counties and a U.S. peer set matched on size, metro character and a major public university — the honest comparison, not a flattering one.

How Pima/Tucson compares — every issue, every peer

Same six issues, four benchmarks. Bars below the Pima/Tucson line are where we lead; bars above it are the gap. Toggle a peer group on or off.

Coach Lucy
💡 Coach Lucy's Coaches Tip

Read the gaps, not the scores. A 44 means nothing on its own. A 44 when Arizona peers are at 47 and the PHIT network is at 66 means we are 22 points behind what's demonstrably achievable — that's the sentence that moves a Supervisor. Always quote the gap to the PHIT network: it proves the number isn't fixed, because somebody else already fixed it.

Gap to the best — where the 22 points are

Distance from Pima/Tucson to the PHIT network best-practice benchmark. This is your priority list, in order.

Coach Lucy
💡 Coach Lucy's Coaches Tip

Childcare is the biggest single gap — and it's the one the Commission has named at every retreat and on the 6/3 list. That's not a coincidence; it's a mandate. If the Commission picks one thing to put in front of the Board of Supervisors this year, the data says childcare. Bring the gap, not the grievance.

Where the data comes from — PHIT Datahub binding

Every indicator on this card is bound to a named feed. This is the wiring list: what's auto-pullable today, what needs a request, and what only the Commission can report.

Coach Lucy
💡 Coach Lucy's Coaches Tip

Most of this is already public — you just have to go get it. The federal layer (Census ACS, CDC, HRSA) is downloadable today with no permission needed. The friction is in the middle layer: court records, the DES subsidy waitlist, and the clerks' board rosters need a request. That's a Letter from the Chair, not a grant. And two indicators are entirely ours — My Girl Power enrollment and the PCTWC roster. We can move those tomorrow.

How these scores are built

⚠️ Read this before you quote a number.

The scores currently shown are illustrative sample values to demonstrate the format. They are not measured results, and no commissioner should cite them publicly yet. What is real is the method below: the indicators, the sources, and the weights. Once these are wired to the PHIT Datahub, the same math runs on live public data and the numbers become citable.

The formula

Score = Σ ( weighti × normalizedi ) × 100

Each indicator is min–max normalized against a national reference range, so every measure lands on the same 0–100 scale. Indicators where less is better (poverty, uninsured rate, DV incidents) are inverted, so higher is always better. Weights sum to 100% within each issue.

Coach Lucy
💡 Coach Lucy's Coaches Tip

Two of these indicators are ours to move directly. "Girls in leadership programs" is literally My Girl Power enrollment, and "PCTWC seats filled" is the Commission's own roster — 15 of 20 = 75%. Fill the five open seats and the Civic Representation score rises on its own. That is the rarest thing in advocacy: a number you control.

Benchmark Table & Gap-to-Peer

The "gap" column is Pima/Tucson minus U.S. county peers — negative (red) is where the commission should press hardest.

IssuePima/TucsonAZ PeersU.S. PeersPHIT PeersGap vs U.S.

Sample data for demonstration. Production scoring is computed by the My Girl Power Squad's methodology from public datasets (county health rankings, BLS/pay data, childcare deserts, civic participation) via the PHIT Datahub, refreshed quarterly. Peer sets: AZ = comparable Arizona counties; U.S. = similarly-sized counties nationally; PHIT = counties active in The Force for Health network.

How the score is calculated — the short version

Coach Lucy
💡 Coach Lucy · How this works

Every score is a weighted average of public indicators, on a 0–100 scale.

Step 1 — Collect. Each issue has 4–5 indicators, pulled from public data (see the table above for the exact table and agency).

Step 2 — Normalize. Each indicator is min–max normalized against a national reference range, so a childcare-slot count and a poverty percentage can live on the same scale:
normalized = (value − min) ÷ (max − min)

Step 3 — Flip the bad ones. Where less is better — poverty, uninsured rate, DV incidents, childcare cost — the value is inverted (1 − normalized), so higher always means better. No exceptions, no asterisks.

Step 4 — Weight and sum. Score = Σ ( weighti × normalizedi ) × 100 Weights sum to 100% within each issue and are listed on every row above.

Step 5 — The overall index is the simple average of the six issue scores. Nothing is hidden and nothing is smoothed.

⚠️ The one thing you must say out loud: the numbers on this page are sample values until the PHIT Datahub is connected. The method is real, the sources are real, the weights are real. The scores are not yet measured. Never quote one to a Supervisor until the badge at the top of the data panel turns green.