Fayette County Ohio GIS 2010 Census Block Groups and Median Household Income. The information provided is for reference only and subject to independent verification. User assumes all responsibility for its use.https://datausa.io/profile/geo/fayette-county-oh
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Institutions of higher education (IHE) throughout the United States have a long history of acting out various levels of commitment to diversity advancement, equity, and inclusion (DEI). Despite decades of DEI “efforts,” the academy is fraught with legacies of racism that uphold white supremacy and prevent marginalized populations from full participation. Furthermore, politicians have not only weaponized education but passed legislation to actively ban DEI programs and censor general education curricula (https://tinyurl.com/antiDEI). Ironically, systems of oppression are particularly apparent in the fields of Ecology, Evolution, and Conservation Biology (EECB)–which recognize biological diversity as essential for ecological integrity and resilience. Yet, amongst EECB faculty, people who do not identify as cis-heterosexual, non-disabled, affluent white males are poorly represented. Furthermore, IHE lack metrics to quantify DEI as a priority. Here we show that only 30.3% of US-faculty positions advertised in EECB from Jan 2019-May 2020 required a diversity statement; diversity statement requirements did not correspond with state-level diversity metrics. Though many announcements “encourage women and minorities to apply,” empirical evidence demonstrates that hiring committees at most institutions did not prioritize an applicant’s DEI advancement potential. We suggest a model for change and call on administrators and faculty to implement SMART (i.e., Specific, Measurable, Achievable, Realistic, and Timely) strategies for DEI advancement across IHE throughout the United States. We anticipate our quantification of diversity statement requirements relative to other application materials will motivate institutional change in both policy and practice when evaluating a candidate’s potential “fit”. IHE must embrace a leadership role to not only shift the academic culture to one that upholds DEI, but to educate and include people who represent the full diversity of our society. In the current context of political censure of education including book banning and backlash aimed at Critical Race Theory, which further reinforce systemic white supremacy, academic integrity and justice are more critical than ever. Methods Here we investigated the (lack of) process in faculty searches at IHE for evaluating candidates’ ability to advance DEI objectives. We quantified the prevalence of required diversity statements relative to research and/or teaching statements for all faculty positions posted to the Eco-Evo Jobs Board (http://ecoevojobs.net) from January 2019 - May 2020 as a proxy for institutional DEI prioritization (Supplement). We also mapped the job posts that required diversity statements geographically to gauge whether and where diversity is valued in higher education across the US. Data analysis We pulled all faculty jobs posted on Eco-Evo jobs board (http://ecoevojobs.net) from Jan 1, 2019, to May 31, 2020. For each position, we recorded the Location (i.e., state), Subject Area, Closing Date, Rank, whether or not the position is Tenure Track, and individual application materials (i.e., Research statement, Teaching statement, combined Teaching and Research statement, Diversity statement, Mentorship statement). Of the 543 faculty positions posted during this time, we eliminated 299 posts because the web links were broken or application information was no longer available (i.e., “NA”), leaving 244 faculty job posts. For each of the retained posts, we coded the requirement of teaching, research, diversity, and/or mentorship statements as follows:
"Yes” = statement required “No” = statement not required “Other” = application materials did not explicitly require a Diversity Statement (i.e., option or suggested that applicants include a statement on diversity and inclusion as a component of their teaching and/or research statement or in their cover letter)
Data visualization We created a Sankey diagram using Sankey Flow Show (THORTEC Software GmbH: www.sankeyflowshow.com) to compare diversity and representation from the general population, through (Science, Technology, Engineering, and Mathematics) STEM academia (a career hierarchy often referred to as the “leaky pipeline”). We procured population data from the US Census Bureau (US Department of Commerce: https://www.census.gov/quickfacts/fact/table/US/PST045219) and quantified the diversity/representation in Conservation Biology (https://datausa.io/profile/cip/ecology-evolution-systematics-population-biology#demographics) and Ecology (https://datausa.io/profile/cip/conservation-biology) using Data USA (developed by Deloitte Touche Tohmatsu Limited and Datawheel). We used the 2015 Diversity Index (produced by PolicyLink and the USC Program for Environmental and Regional Equity: https://nationalequityatlas.org/indicators/Diversity_index/Ranking:33271/United_States/false/Year(s):2015/) to quantify relative ethnic diversity per state, and graphed Figure 2B using the tidyverse, rgdal, broom, and rgeos packages in R (see Base code used to produce Figure 2 in R, below). The Diversity index measures the representation of White, Black, Latino, Asian/Pacific Islander, Native American, and Mixed/other race in a given population. A maximum possible diversity score (1.79) would indicate even representation of all ethnic/racial groups. We checked all figures using the Color Blindness Simulator (ColBlindor: https://www.color-blindness.com/coblis-color-blindness-simulator/) to maintain inclusivity.
Fayette County Ohio Selected Economic and Demographic Data by Political Subdivision.The information provided is for reference only and subject to independent verification. User assumes all responsibility for its use. https://datausa.io/profile/geo/fayette-county-oh
The Consumer Demographic database is comprised of over 80 sources and includes over 400 different data points for each individual in a household with complete PII. The fields provided include demographics, psychographic, lifestyle criteria, buying behavior, and real property identification.
Each record is ranked by confidence and only the highest quality data is used. The database is multi-sourced and contains both compiled and originated U.S. data. Additionally, the data goes through intensive cleansing including deceased processing and NCOA.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
Unlock precise, high-quality GIS data covering 43M+ verified locations across the USA. With 50+ enriched attributes including coordinates, building structures, and spatial geometry our dataset provides the granularity and accuracy needed for in-depth spatial analysis. Powered by AI-driven enrichment and deduplication, and backed by 30+ years of expertise, our GIS solutions support industries ranging from mapping and navigation to urban planning and market analysis, helping businesses and organizations make smarter, data-driven decisions.
Key use cases of GIS Data helping our customers :
Resident/Occupant Database
Alesco Data's Resident/Occupant Database includes over 143 million addresses and reaches virtually 100% of every U.S. household in every Zip Code throughout the country. With newly added business addresses, you now have the option to reach every postal delivery point in the country.
This address file is updated every month in conjunction with the U.S. Post Office, making it the freshest, most deliverable mailing list available. You have the ability to order addresses by Carrier Route, ZIP, County or State.
Our Resident/Occupant Database contains names of residents on approximately 80% of the file and are available when requested. Otherwise, records are addressed to "Resident" or “Boxholder”. This file is ideal for saturation mailings. Each list is “walk sequenced” at the time of order and qualifies for the lowest available postage rates.
ESRI Data & Maps contains many types of map data at many scales of geography, and the entire dataset can be read directly from the DVD in the media kit. All vector data is provided in Smart Data Compression (SDC) format. The HTML-based Help system contains information about Data & Maps and StreetMap North America, including a complete list of the redistribution rights for each dataset. Please review this information carefully before redistributing any of this data.http://www.library.utoronto.ca/datalib/datart/maplib/data/ESRI/Streetmap_na/help.htm
Unlock the power of 43M+ verified locations across the USA with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.
Key use cases of Geospatial data have helped our customers in several areas:
Unlock powerful insights with our BatchService Homeowner and Household Demographic Data. Access 35+ data points across 107M+ properties, perfect for targeted marketing, research, and analysis. Dive into detailed homeowner profiles and household characteristics with ease.
BatchData offers cutting-edge API and dataset solutions designed to empower businesses with comprehensive data insights. BatchData provides access to a vast array of information, including detailed homeowner and household demographic across millions of properties. With seamless integration via our API, you can effortlessly incorporate rich data into your websites, applications, and analytics tools. This enables precise lead generation, targeted marketing, and in-depth market analysis, helping you make informed decisions and drive growth.
Explore the extensive data we points we have below to understand the diverse and detailed information included in our dataset: - The property owner's age - Primary occupant is a business owner? - The primary occupant's child count - The household discretionary income - The primary occupant's gender - Primary occupant has children? - Occupants are owners or renters? - Household size - Household income - Primary occupant's individual education - Primary occupant's occupation - Primary occupant's investments - Primary occupant's marital status - Primary occupant is a millionaire? - Household net worth - Primary occupant is a pet owner? - Primary occupant recently divorced? - Primary occupant recently moved? Month? Year? - Property owner's religious affiliation - Primary occupant single parent? - Primary occupant smoker?
For every successful marketing strategy and increase in ROI, accurate data is the key for every company. VentiveIQ's data helps companies to reach the consumer at an individual level. We provide more than 100 plus consumer attributes including gender, income, marital status, pet owners and many more. The consumer data can further be tied to unique MAID's which can help companies with digital marketing.
New Homeowner Data is a subset of our comprehensive property intelligence database that can be segmented by specific property criteria, household demographics, mortgage, and real estate portfolio information.
Companies in the home services, financial products, and consumer products industries use BatchData to identify new homeowners who have purchased a property in the last 90 days and uncover their direct phone number, email, and mailing address for timely marketing of products and services new homeowners need. New homeowner data can also be segmented property type (residential real estate or commercial real estate), length of ownership, owner occupancy status, and more!
New homeowner data is available in a variety of data delivery and data enrichment modes: API (you pull data from us using an API), webhook (we push data to you using an API), AWS S3 upload (we deliver the data to you), S3 download (you download the data from our S3 bucket), SFTP.
BatchData is both a data and technology solution helping companies in and around the real estate ecosystem achieve faster growth. BatchData specializes in providing accurate contact information for US property owners, including in-depth intelligence and actionable insights related to their property. Our portfolio of products, services, and go-to-market expertise help companies identify their target market, reach the right prospects, enrich their data, and power their products and services.
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Leverage high-quality B2B data with 468 enriched attributes, covering firmographics, financial stability, and industry classifications. Our AI-optimized dataset ensures accuracy through advanced deduplication and continuous updates. With 30+ years of expertise and 1,100+ trusted sources, we provide fully compliant, structured business data to power lead generation, risk assessment, CRM enrichment, market research, and more.
Key use cases of B2B Data have helped our customers in several areas :
The US Consumer Audience Segmentation file has 280 million+ U.S. consumers clustered into bubbles based on their household income, generation, marital status, and environment (urban-suburban or rural-town). These key traits are extremely useful in understanding consumers and their purchasing behaviors at a high level. Each Bubble utilizes different combinations of attributes to organize and observe consumers on an increasingly granular level.
We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used. This file contains over 280 million records.
Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
The US Consumer IP Address file contains information on the location and observation dates of IP addresses tied to individuals in the Consumer Database. It is updated monthly from a database containing billions of IP<>email linkages.
We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used.
Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
Demographic and PII data (including emails, phone numbers, and addresses) for the US Millennial and Gen Z population segments. Fully opt-in and CCPA compliant (direct submission from the individuals). 30 million+ population.
High success and conversion rates for direct marketing, targeted ads, identity verification, and demographic research.
This data can be merged into the BIGDBM Consumer dataset or have specific data fields appended from the BIGDBM Consumer dataset.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
The Consumer Mobile Device file contains MAIDs connected to an individual in the Consumer Database. The fields available include latitude and longitude, device type, hashed emails, and plain-text emails.
This is updated monthly from a database containing billions of MAID<>email linkages.
We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used.
Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
The US Consumer Commercial Property/Real Estate file has 30 million+ non-residential properties which include property characteristics, site details, purchase details, tax details, and ownership information.
We have developed this file to be tied to our Consumer and B2B Database so additional data fields can be applied to the owners. Each record is ranked by confidence and only the highest quality data is used.
Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
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Fayette County Ohio GIS 2010 Census Block Groups and Median Household Income. The information provided is for reference only and subject to independent verification. User assumes all responsibility for its use.https://datausa.io/profile/geo/fayette-county-oh