Existing Conditions Signals Overview – Social Explorer

What Signals are

The What stands out section at the top of your brief turns the full report into the few things to know first. It is a ranked list of findings: the tool computes a fixed set of indicators from your brief’s data, flags the ones that cross an established planning benchmark, and ranks them so the most pressing appear at the top.

The section header names the place the findings describe (for example, “What stands out in Burlington city”), which matters when your brief compares several geographies. The info icon beside the header gives a short version of this article, with a link back here.

Signals are a starting point for review. They point you to where to look, and the detail behind every one lives in the section it comes from.

How findings are calculated

Each signal is computed for your study area, the target geography your brief is built around, from the same data that fills the rest of the report. A signal appears only when its value crosses a set benchmark. Signals that stay within the normal range are not shown in the read view, though they are still computed and stored (you can see them in Customize, described below).

Flagged signals are ranked by three things:

Severity: how far the value sits past its benchmark (critical, high, or moderate). This is the main driver of the order.
How far it diverges from your comparison areas: if the value is 15% or more worse than the average of your comparison geographies (for example the metro area, county, and state), the signal is pushed up the list.
Direction over time: where a 10-year trend is available, a worsening trend pushes the signal up the list.

When two signals score the same, they keep the order they appear in the catalog, so the list is stable between runs.

Signals are screening indicators, not determinations. They are meant to prioritize your review, not to settle a question on their own. Margins of error are not shown on the flags; where reliability matters for a small area, review the underlying section data.

The severity levels

Each signal carries a color that shows how far past its benchmark it sits:

Critical (red): well above the benchmark; review first.
High (orange): above the benchmark.
Moderate (amber): at the lower flag level. Amber still marks a finding worth noting, within a normal-to-moderate range. It does not mean “good”; it means the value reached the first threshold but not the higher ones.

Hover over a signal’s value to see its full threshold ladder: every level, its cutoff, and which one the value currently sits in. On wider screens, each row also shows a small band track on the right that places the value within the severity bands.

The legend at the bottom of the section lists only the levels actually present in your brief, along with the data sources behind the flagged signals and the comparison areas used.

The signals we track

The Existing Conditions brief tracks nine signals across four topics. For each one, here is what it measures, what it commonly indicates, who is counted, where the data comes from, and when it is flagged.

Housing

Renter cost burden (30%+ of income)

What it is: Share of renter households paying 30% or more of household income on gross rent (rent plus utilities).
What it means: HUD classifies households at this level as cost-burdened. A higher share is commonly associated with greater risk of housing instability and displacement.
Who’s counted: All renter-occupied households for which rent as a share of income is calculated.
Source: U.S. Census Bureau, American Community Survey (ACS) 5-year estimates.
When it’s flagged: At 38% (moderate), 44% (high), 49% (critical).
Trend: Compared against the ACS 5-year period about a decade earlier. A rise of more than 1 percentage point is marked worsening.

Owner cost burden (30%+ of income)

What it is: Share of owner households paying 30% or more of household income on selected monthly owner costs, with and without a mortgage.
What it means: The owner-side counterpart to renter cost burden. A higher share is commonly associated with strain on existing homeowners, which is often read alongside the renter picture rather than on its own.
Who’s counted: All owner-occupied households for which owner costs as a share of income are calculated.
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: At 18% (moderate), 22% (high), 25% (critical). These cutoffs are the 50th, 75th, and 90th percentiles of the owner distribution across U.S. counties, so an owner flag means roughly the same relative strictness as a renter flag.
Trend: Same 10-year comparison as renter cost burden.

Renter-majority jurisdiction

What it is: Share of occupied homes that are renter-occupied rather than owner-occupied.
What it means: Above 50% marks a renter-majority jurisdiction, a context where rental-market conditions and tenant protections are often central planning considerations.
Who’s counted: All occupied housing units.
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: At 50% (moderate), 55% (high), 60% (critical).

Pre-1960 housing stock (lead-paint risk)

What it is: Share of occupied homes built before 1960.
What it means: Older housing is more likely to contain lead-based paint. This is a screening indicator for lead-exposure risk, not a confirmation of it.
Who’s counted: All occupied housing units, by the year the structure was built.
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: At 25% (moderate), 30% (high), 35% (critical).

Low vacancy rate (tight housing market)

What it is: Share of all housing units that are vacant.
What it means: A low vacancy rate is commonly read as a tight housing market with limited available supply.
Who’s counted: All housing units (occupied plus vacant).
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: When vacancy is below 5%. This is the one signal where a lower value is the worse one, and it has a single level.

Rent growth outpacing income (10-year)

What it is: The gap between 10-year growth in median gross rent and 10-year growth in median household income, in percentage points.
What it means: A positive gap means rents rose faster than incomes over the period, commonly associated with worsening affordability. Reported in nominal terms.
Who’s counted: Jurisdiction median gross rent and median household income, compared across two ACS 5-year periods about a decade apart.
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: At +3 points (moderate) and +10 points (high). Shown only when positive; always marked as worsening.

Equity

Poverty rate

What it is: Share of people whose household income is below the federal poverty level.
What it means: A higher poverty rate is commonly associated with greater need across housing, health, and economic-support programs.
Who’s counted: Population for whom poverty status is determined (excludes most people in institutions and college dormitories).
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: At 15% (moderate), 20% (high), 25% (critical).

Economic

Elevated unemployment

What it is: Share of the civilian labor force age 16 and older that is unemployed.
What it means: An elevated rate is commonly associated with greater economic distress and demand for workforce and support services.
Who’s counted: Civilian labor force age 16 and older.
Source: U.S. Census Bureau, ACS 5-year estimates.
When it’s flagged: At 5% (moderate), 6% (high), 10% (critical).

Safety

Total Crime Index

What it is: A composite index of total reported crime where 100 equals the U.S. median.
What it means: A value above 100 indicates total crime higher than the national median (for example, 130 is about 30% above). It is an index, not a count, and is not directly comparable across places of very different sizes.
Who’s counted: Modeled crime estimates for the area, indexed to the U.S. median (100).
Source: Social Explorer Crime Index.
When it’s flagged: At 125 (moderate), 130 (high), 135 (critical).
Note: The brief flags the composite index only. Property crime and violent crime are components of that same index, so flagging all three counted one theme three times and crowded the list. The property and violent detail is still in the Safety section table.

Adjusting thresholds

The default cutoffs are national benchmarks. When they do not fit local context, you can change them for a brief.

On the What stands out card, select Customize. The list expands to show every signal that was computed, including ones that did not flag, which are dimmed and tagged “Not flagged.”
A panel opens on the right with one card per signal: a numeric field for Moderate, High, and Critical, each prefixed with the comparison the level uses (≥ for most signals, < for low vacancy).
Type new cutoffs. Values recolor in the list as you type, so you can see what would flag before committing. Clear a field to turn that level off.
Select Apply to save. The list re-ranks on apply, not while you type.

A few rules to know:

Cutoffs must get stricter as severity rises: moderate, then high, then critical. For low vacancy the cutoffs descend instead. A contradictory set is outlined in red, the value badge goes neutral, and Apply stays disabled until you fix it.
Undo on a card drops your unsaved edits to that signal. Reset to default writes the template’s original cutoffs into the fields, which you then apply.
Reset thresholds in the card’s toolbar restores the defaults for every customized signal at once. It saves immediately, so it asks for confirmation first.
Closing the panel with unsaved edits asks before discarding them.

What happens after you apply:

Changes are saved to that brief, not to your account or to the template. Other briefs keep the defaults.
Everyone with access to the brief sees the adjusted thresholds, and the change is recorded in the brief’s activity.
Custom cutoffs are kept when the brief is regenerated, so a refresh does not silently undo your tuning.
Exports use the thresholds in effect when you export.
Thresholds cannot be edited while a brief is generating. Wait for the run to finish, then adjust.

Signals in exports

Key Findings is the first content block of a Word or PDF export, with the same values, severity colors, trend and comparison notes, source line, and legend as the screen. Excel exports get a Key Findings sheet with one row per ranked signal and the value as a real number.

In the export dialog, Include Key Findings controls whether the block is written. Exporting Key Findings on its own, with no sections selected, is valid.

Data sources and freshness

Signals draw from the U.S. Census Bureau’s American Community Survey (5-year estimates) and the Social Explorer Crime Index. The 10-year comparisons use the ACS 5-year release from about a decade earlier. Your brief shows the exact data vintage in use, and the American Community Survey data is refreshed each year as a new 5-year release is published.

The source line under the signals lists only the sources behind the signals actually flagged in your brief, grouped by publisher.

Common questions

Why is a moderate finding amber?

Amber marks a finding at the lowest flag level, still worth noting but within a normal-to-moderate range. It is a severity color, not a judgment that the value is good.

Why don’t you show a margin of error?

Signals are screening flags meant to prioritize review, so they show the value and its severity, not statistical margins. When reliability matters for a small area, review the underlying section data.

Can I change the thresholds?

Yes. Select Customize on the What stands out card and edit the cutoffs, as described in the “Adjusting thresholds” section above. Changes apply to the brief you are working in and are kept when it is regenerated.

Why is cost burden measured at 30% and not 50%?

30% of income is HUD’s standard cost-burden definition and the one most planning documents cite, so the signal now uses it for both renters and owners. The 50% severe-burden breakdown is still reported in the Housing section tables.

What if no signals appear?

That is a valid result. It means no indicator crossed its threshold for your area. Open Customize to see the computed values behind that result, and review the section data for detail.

Why these comparison areas?

Comparisons use the other geographies in your brief, typically the ones that enclose your target area (for example its metro area, county, and state). The line under the signals names the specific comparison areas used.