{EXPLORE_COPY.NOTE_ON_TERRITORIES.PARA_1}
{EXPLORE_COPY.NOTE_ON_TERRITORIES.PARA_2}
+{EXPLORE_COPY.NOTE_ON_TERRITORIES.PARA_3}
diff --git a/client/src/components/SurveyButton/SurveyButton.module.scss b/client/src/components/SurveyButton/SurveyButton.module.scss index cda9d8cc..b2a2c2ad 100644 --- a/client/src/components/SurveyButton/SurveyButton.module.scss +++ b/client/src/components/SurveyButton/SurveyButton.module.scss @@ -15,12 +15,17 @@ @include u-height(6); z-index: 2; - @include u-text("gray-90"); + @include u-text("blue-70v"); @include u-bg("yellow-20v"); &:hover { @include u-bg("yellow-20"); @include u-text("gray-90"); } + + .launchIcon { + height: .8rem; + // @include u-margin-bottom('neg-05'); + } } } diff --git a/client/src/components/SurveyButton/SurveyButton.module.scss.d.ts b/client/src/components/SurveyButton/SurveyButton.module.scss.d.ts index b8c5cbc2..5e9ed98f 100644 --- a/client/src/components/SurveyButton/SurveyButton.module.scss.d.ts +++ b/client/src/components/SurveyButton/SurveyButton.module.scss.d.ts @@ -2,6 +2,7 @@ declare namespace SurveyButtonNamespace { export interface ISurveyButtonScss { surveyButton: string; surveyButtonContainer: string; + launchIcon: string; } } diff --git a/client/src/components/SurveyButton/SurveyButton.tsx b/client/src/components/SurveyButton/SurveyButton.tsx index f2663706..7734c6c3 100644 --- a/client/src/components/SurveyButton/SurveyButton.tsx +++ b/client/src/components/SurveyButton/SurveyButton.tsx @@ -6,6 +6,9 @@ import * as styles from './SurveyButton.module.scss'; import * as CONTACT_COPY from '../../data/copy/contact'; import J40MainGridContainer from '../J40MainGridContainer'; +// @ts-ignore +import launchIcon from '/node_modules/uswds/dist/img/usa-icons-bg/launch--blue-70v.svg'; + export const onClickHandler = () => { Object.assign(document.createElement('a'), {target: '_blank', href: 'https://www.surveymonkey.com/r/cejst-survey'}).click(); }; @@ -19,6 +22,11 @@ const SurveyButton = () => { className={styles.surveyButton} onClick={() => onClickHandler()}> {intl.formatMessage(CONTACT_COPY.PAGE_INTRO.SURVEY_TEXT)} +Note:{` - Unlike most of the other datasets, high values of this indicator indicate low burdens. - For percentile calculations, the percentile is calculated in reverse order, so that the tract with - the highest median income relative to area median income (lowest burden on this measure) is at the - 0th percentile, and the tract with the lowest median income relative to area median income + Unlike most of the other datasets, high values of this indicator indicate low burdens. + For percentile calculations, the percentile is calculated in reverse order, so that the tract with + the highest median income relative to area median income (lowest burden on this measure) is at the + 0th percentile, and the tract with the lowest median income relative to area median income (highest burden on this measure) is at the 100th percentile. `}
, }} />, usedIn: CATEGORIES.HEALTH_BURDENS.METHODOLOGY, - responsibleParty: RESPONSIBLE_PARTIES.CDC_SLEEP, - dateRange: DATE_RANGE.TEN_PLUS_5, + responsibleParty: RESPONSIBLE_PARTIES.CDC, + sources: [ + { + source: SOURCE_LINKS.CDC_SLEEP, + availableFor: AVAILABLE_FOR.ALL_US_DC, + }, + ], }, { domID: 'low-med-inc', @@ -1076,8 +1237,17 @@ export const INDICATORS = [ description= {'description text for workforce dev'} />, usedIn: CATEGORIES.WORKFORCE_DEV.METHODOLOGY, - responsibleParty: RESPONSIBLE_PARTIES.CENSUS_ACS, - dateRange: DATE_RANGE.FIFETEEN_PLUS_4, + responsibleParty: RESPONSIBLE_PARTIES.CENSUS, + sources: [ + { + source: SOURCE_LINKS.CENSUS_ACS_15_19, + availableFor: AVAILABLE_FOR.ALL_US_DC_PR, + }, + { + source: SOURCE_LINKS.CENSUS_ACS_10, + availableFor: AVAILABLE_FOR.AS_NMI, + }, + ], }, { domID: 'ling-iso', @@ -1085,13 +1255,19 @@ export const INDICATORS = [ description:
For general feedback, email
Help improve the site & data
+
diff --git a/client/src/pages/__snapshots__/index.test.tsx.snap b/client/src/pages/__snapshots__/index.test.tsx.snap
index 1e1368c7..d419da4a 100644
--- a/client/src/pages/__snapshots__/index.test.tsx.snap
+++ b/client/src/pages/__snapshots__/index.test.tsx.snap
@@ -319,8 +319,11 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
In
Executive Order 14008
@@ -395,8 +398,11 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
Read more about the Justice40 Initiative in President Biden’s
Executive Order 14008
@@ -587,7 +593,8 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
class="j40-aboutcard-sm-link"
>
Help improve the site & data
+
diff --git a/client/src/pages/__snapshots__/methodology.test.tsx.snap b/client/src/pages/__snapshots__/methodology.test.tsx.snap
index 2808327d..5d885144 100644
--- a/client/src/pages/__snapshots__/methodology.test.tsx.snap
+++ b/client/src/pages/__snapshots__/methodology.test.tsx.snap
@@ -841,29 +841,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -875,37 +884,46 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
- Percent of agriculture value at risk from losses due to natural hazards. Calculated by dividing
- the agriculture value at risk in a census tract by the total agriculture value in that census
- tract. Fourteen natural hazards that have some link to climate change include: avalanche,
- coastal flooding, cold wave, drought, hail, heat wave, hurricane, ice storm, landslide,
- riverine flooding, strong wind, tornado, wildfire, and winter weather.
+ Percent of agriculture value at risk from losses due to natural hazards such as the fourteen
+ natural hazards that have some link to climate change including: avalanche, coastal flooding,
+ cold wave, drought, hail, heat wave, hurricane, ice storm, landslide, riverine flooding, strong
+ wind, tornado, wildfire, and winter weather. Calculated by dividing the agriculture value at risk in
+ a census tract by the total agriculture value in that census tract.
+
@@ -917,38 +935,47 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
- Percent of building value at risk from losses due to natural hazards. Calculated by dividing the
- building value at risk in a census tract by the total building value in that census tract.
- Fourteen natural hazards that have some link to climate change include: avalanche,
- coastal flooding, cold wave, drought, hail, heat wave, hurricane, ice storm, landslide,
- riverine flooding, strong wind, tornado, wildfire, and winter weather.
-
+ Percent of building value at risk from losses due to natural hazards such as the fourteen
+ natural hazards that have some link to climate change including: avalanche, coastal flooding,
+ cold wave, drought, hail, heat wave, hurricane, ice storm, landslide, riverine flooding, strong
+ wind, tornado, wildfire, and winter weather. Calculated by dividing the building value at risk in
+ a census tract by the total building value in that census tract.
+
-
@@ -1009,29 +1045,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
Average annual energy cost ($) divided by household income.
- Rate relative to the population in fatalities and injuries due to natural hazards each year.
- Fourteen natural hazards that have some link to climate change include: avalanche, coastal
- flooding, cold wave, drought, hail, heat wave, hurricane, ice storm, landslide, riverine
- flooding, strong wind, tornado, wildfire, and winter weather.
- Population loss is defined as the Spatial Hazard Events and Losses or National Centers
- for Environmental Information’s (NCEI) reported number of fatalities and injuries caused by the
- hazard occurrence. To combine fatalities and injuries for the computation of population loss value,
- an injury is counted as one-tenth (1/10) of a fatality. The NCEI Storm Events Database
- classifies injuries and fatalities as direct or indirect. Both direct and indirect injuries
- and fatalities are counted as population loss. This total number of injuries and fatalities
- is then divided by the population in the census tract to get a per-capita rate of population risk.
+ Rate relative to the population in fatalities and injuries due to natural hazards each year such as
+ the fourteen natural hazards that have some link to climate change including: avalanche,
+ coastal flooding, cold wave, drought, hail, heat wave, hurricane, ice storm, landslide,
+ riverine flooding, strong wind, tornado, wildfire, and winter weather. Population loss is defined
+ as the Spatial Hazard Events and Losses or National Centers for Environmental Information’s
+ (NCEI) reported number of fatalities and injuries caused by the hazard occurrence. To
+ combine fatalities and injuries for the computation of population loss value, an injury is counted
+ as one-tenth (1/10) of a fatality. The NCEI Storm Events Database classifies injuries and fatalities
+ as direct or indirect. Both direct and indirect injuries and fatalities are counted as population
+ loss. This total number of injuries and fatalities is then divided by the population in the
+ census tract to get a per-capita rate of population risk.
+
+
@@ -1047,33 +1092,42 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1089,32 +1143,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1131,31 +1191,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1167,37 +1234,43 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
- The percent of households in a census tract that are both earning less than 80% of HUD Area Median
- Family Income by county and are paying greater than 30% of their income to housing costs.
+ The percent of households in a census tract that are both earning less than 80% of HUD Area Median
+ Family Income by county and are paying greater than 30% of their income to housing costs.
+
@@ -1209,34 +1282,43 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
- Percent of housing units built pre-1960, used as an indicator of potential lead paint exposure in
+ Percent of housing units built pre-1960, used as an indicator of potential lead paint exposure in
tracts with median home values less than 90th percentile
+
@@ -1252,29 +1334,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1291,32 +1382,42 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1329,35 +1430,42 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
Count of proposed or listed NPL - also known as superfund - sites within 5 km (or nearest one
- beyond 5 km), each divided by distance in kilometers.
+ beyond 5 km), each divided by distance in kilometers.
+
@@ -1374,31 +1482,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1410,37 +1525,43 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
- Risk-Screening Environmental Indicators (RSEI) modeled Toxic Concentrations at
+ Risk-Screening Environmental Indicators (RSEI) modeled Toxic Concentrations at
stream segments within 500 meters, divided by distance in kilometers (km).
+
@@ -1452,37 +1573,44 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
- Weighted percent of people who answer “yes” to both of the following questions: “Have you ever
+ Weighted percent of people who answer “yes” to both of the following questions: “Have you ever
been told by a doctor, nurse, or other health professional that you have asthma?” and the question
“Do you still have asthma?”
+
@@ -1500,31 +1628,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1542,31 +1677,38 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
+
@@ -1585,10 +1727,10 @@ exports[`rendering of the DatasetContainer checks if various text fields are vis
Note:
- Unlike most of the other datasets, high values of this indicator indicate low burdens.
- For percentile calculations, the percentile is calculated in reverse order, so that the tract with
- the highest median income relative to area median income (lowest burden on this measure) is at the
- 0th percentile, and the tract with the lowest median income relative to area median income
+ Unlike most of the other datasets, high values of this indicator indicate low burdens.
+ For percentile calculations, the percentile is calculated in reverse order, so that the tract with
+ the highest median income relative to area median income (lowest burden on this measure) is at the
+ 0th percentile, and the tract with the lowest median income relative to area median income
(highest burden on this measure) is at the 100th percentile.